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Transcript of Advanced Analytics-Green Team Book
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Introduction Page 1
ANALYTICMETHODS
GREEN TEAM
16 May 2012
INTL 520
Mercyhurst
University
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Introduction Page i
ADVANCED ANALYTICMETHODS
GREEN TEAM
Dean Atkins
Leslie Guelcher
David Krauza
Puru Naidu
Shawn Ruminski
Emily Slegel
Erie, PA
2012 Mercyhurst University, Green Team, Erie, PA
All rights reserved. No part of this book may be reproduced or
transmitted in any form or by any means without written
permission from the author.
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Advanced Analytics: Green Team Methods page ii
Table of Contents
CHAPTER 1:GAP ANALYSIS 4Description 4Strengths 4Weaknesses 5How-To 5Personal Application 6Conclusion 8CHAPTER 2:COST-BENEFIT ANALYSIS 9Description 9Strengths 9Weaknesses 10How-To 11Personal Application 12Conclusion 16Additional Resources 16CHAPTER 3:CONTENT ANALYSIS 18Description 18Strengths 18Weaknesses 19How-To 19Personal Application 21Conclusion 25Additional Resources 25CHAPTER 4:DEPHI METHOD 26Description 26Strengths 26Weaknesses 27How-To 27Personal Application 28Conclusion 30CHAPTER 5:GAME THEORY 31Description 31Strengths 33
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Introduction Page iii
Weaknesses 34How To 34Personal Application 35Conclusion 37CHAPTER 6:COMPARATIVE NEWS FRAME ANALYSIS 38Description 38Strengths 39Weaknesses 39How-To 40Personal Application 41Conclusion 45Further Information 45BIBLIOGRAPHY 47
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Advanced Analytics: Green Team Methods page 4
Chapter 1: Gap Analysis
Dean Atkins
Description
Gap analysis is a method that identifies the difference
(gap) between the current state and a desired end state of
a situation within a business or organization. As an
analytic tool in the intelligence community, gap analysisis focused externally on other countries and entities. The
current state is generally known and the gap analysis can
be used to identify the likely course of action a
target/entity may take in order to get to their desired end
state. Traditionally, gap analysis is internally focused.
Gap analysis can be done in a number of ways and is very
similar to benchmarking.
Strengths
Flexibility. There are a number of different ways to use it. Gap
analysis can be done in a number of ways. It can be applied
quantitatively or qualitatively and can be broken down into
smaller components in a micro approach or applied on a larger
scale in a macro approach.
Can be applied internally or externally. Gap analysis is
traditionally applied internally in order to improve business
methods to a desirable end state from their current position.
The intelligence field requires an external focus and this can be
achieved by using the current state and the desired end state toidentify possible course of action/pathways.
Once gaps are identified, it is easier to come up with
actions/solutions. When gaps are perceived and identifiedit
then becomes a lot easier to provide actions or solutions to a
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Page 5
decision maker. These recommendations are easily rationed
and explained with a clear gap guiding the user.
Weaknesses
There is no standardized way of doing it. With so many waysof using gap analysis, a number of methods can be used to
perceive and demonstrate the gap. It is also hard to conduct and
compare if there are so many ways of implementing the
method.
Doesnt offer a clear estimate.Most analytic techniques offera decision maker a clear estimate. Internally this may be
realistic. However, when applied externally, you are not certain
of the pathways or courses of action a target may use, making
an estimate much harder to be extracted from gap analysis.
Harder to apply externally. Furthermore, externally focused
gap analysis has a lot less data and information that can beutilized. This makes it more challenging to find the current
state, know a targets desired end state and therefore, likely
courses of action to breach the gap between those two states.
How-To
1. Identify the target. Whether it is internal or external,identify the target that you will be applying the gapanalysis to.
2. Identify the current state. Using all possible informationavailable, determine the current position of the target
where they are at.
3. Identify the desired end state. Whether its a statementof their intent or a likely outcome given the informationyou have, determine the desired end state of the target.
What are they trying to achievewhere do they want to
be.
4. Determine what the gaps are between the two states.
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Advanced Analytics: Green Team Methods page 6
The gap between the two states is where the most
flexibility can be applied. In whatever manner
necessary, determine what the gaps are between where
they are at and where they want to be. This may take
into account qualitative or quantitative data in a micro
or macro approach.
5. Interpret how the target may act in order to breach thegap. Using the gaps you have identified, figure out the
likely courses of action the target may take to get from
the current state to the ideal end state. Although these
may not be truly estimative, it can identify possiblepathways or courses of action.
6. Report results. Report the findings back, clearly statingwhat the current state and desired end states were,
followed by the gaps identified and if necessary, likely
courses of action the target may take in order to breach
that gap.
Personal Application
1. Identify the target. I applied gap analysis to the MensSoccer Team at Mercyhurst University. My goal was to
use gap analysis in both the traditional, internal way
and also the intelligence method of focusing on external
actors. Therefore, my secondary targets were the other
PSAC (Pennsylvania State Athletic Conference) teams.
2. Identify the current state. Using Excel and a number ofstatistics, I applied the gap analysis quantitatively to
assess where each team was over the past 3 years.
Qualitatively, I interviewed the current Mercyhurst
Soccer coach to achieve more detail on the internal
current state of the Mercyhurst Mens Soccer Team.3. Identify the desired end state. Building on the
quantitative information gathered, I used the previous
PSAC winners as benchmarks (a similar analytic
technique) and the PSAC Title as the desired end state.
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Internally, I honed in on Mercyhurst and the desired
end statethe PSAC Title.
4. Determine what the gaps are between the two states.I used three methods for determining the gaps between
a teams current state and the desired end state of a
PSAC title.
The first method was externally focused and
concentrated on quantitative data in Excel to look for
trends and correlations between data that resulted in
success. There were a number of factors measured;
record, win percentage, home record, home winpercentage, average attendance, squad size, # of players
in each position, # of coaches, # of players by college
year, # of goals scored and # of goals conceded.
The second method was internally focused and
conducted qualitatively. This involved an interview
with the Mercyhurst Soccer Coach and identified a
number of gaps between their current state and desiredend state of a PSAC title.
The third method was developed from the coachs
interview. Utilizing the gaps identified internally, I
explored how they might be applied externally to the
other teams in the PSAC. This then became an external
approach using a qualitative survey of teams defensiveweaknesses. This was a very specific gap analysis,
focusing just on defensive weaknesses and was
measured on the following weaknesses; counter attacks,
corners, free-kicks, penalties, individual mistakes, out
of position, open play, high line, deep line, red cards,
crosses and through the middle.
5. Interpret how the target may act in order to breach thegap. Using the gaps I identified, I came up with a
number of possible approaches the opposition may take
next season in order to get to the desired end state of a
PSAC title. Furthermore, building on the external and
internal factors, I was able to come up with a number of
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Advanced Analytics: Green Team Methods page 8
recommendations and suggestions for the Mercyhurst
Soccer Coach. Utilizing this data would be very useful
if applied to a Indicators and Warnings analytic
technique (possible future study).
6. Report results. After compiling all the data, I presentedto the Mercyhurst Soccer Coach and the Athletic
Director on my findings and conclusions.
Conclusion
The results of the gap analysis were very useful to the
Mercyhurst Soccer Coach and left a lot of scope forfurther study. The method itself is hard to implement
because there is no set way of doing it. It is hard to give
instructions and a how-to methodology for such an
expansive method. My personal application
demonstrates how easy it is to apply the method in a
variety of ways, yet it is important to define whether
you are applying the method internally or externallybeforehand as I found myself blurring the lines on
multiple occasions during my study.
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Chapter 2: Cost-Benefit Analysis
Leslie Guelcher
Description
Cost-benefit analysis (CBA) is an analytic modifier that
attempts to determine if a project, course of action, or
investment should be selected based on limited investible
funds (Mishan & Quah, 2007, p. 3). The process entailsquantifying both the costs and the benefits of a project. It
can be used to reduce uncertainty.
CBA is traditionally used in one of two settings: as an
economic analysis to determine the social benefit of a
public undertaking or as an accounting function for
private enterprises to determine the opportunity costs fora set of projects or decisions (Mishan & Quah, 2007, p.
5).
For economic problems, the cost of a proposal is weighed
as societys cost while the benefits are regarded as social
benefits to determine if a project will result in a netsocial benefit, where benefit cost = net value
(Robinson, 1993, p. 924). At the firm level, the costs are
the actual, or estimated, costs of the project to the firm
alone. Similarly, the benefits are those accrued only to the
firm within the framework of the project being examined
(Sonnenreich, Albanese, & Stout, 2006, p. 55).
Strengths
Cost benefit analysis is simple to implement when using
quantitative data. When conducting CBA using project costs
and benefits that have set financial numbers attached to the
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Advanced Analytics: Green Team Methods page 10
project, it is a simple matter of inputting all costs and then
associated benefits to derive a net value for the project.
CBA reduces uncertainty. The process of listing all potential
costs and quantifying the benefits allows an analyst to verify a
project has considered the true costs of both inputs (costs) and
outputs (benefits). Using brainstorming, expert testimony or
other techniques to generate a list of costs and benefits aids the
process.
Examples of using CBA are plentiful. Because CBA has beenused in both accounting and economics for decades, there are
plenty of examples of academic articles, books, and
downloadable spreadsheet templates to aid in preparing the
analysis.
Methods for determining costs and benefits are available. A
myriad of journal articles and other publications exist thatdetail procedures for arriving at the costs and benefits for a
specific project. For instance, in my application of CBA I
found several articles that helped determine which factors to
include as costs and benefits.
Weaknesses
Qualitative data can be manipulated. To work in CBA,
qualitative data must be changed to quantitative data. Using a
range for the data helps mitigate the bias that could permeate
the analysis. Otherwise, it is easy to underestimate costs while
overestimating benefits, which leads to faulty conclusions.
CBA is not a stand-alone answer. When using qualitative data,other modifiers are needed in conjunction with CBA in order to
transfer the ideas of qualitative to the numbers needed in
quantitative.
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How-To
1. Identify the project, course of action or investment to beanalyzed. The project to be analyzed will usually be
defined by decision-makers. It can be a questioncomparing two potential solutions or a singular
investment that the analyst is tasked with determining
its projected usefulness/benefit.
2. Choose appropriate modifiers. Additional modifiersshould be used to effectively generate a complete list of
benefits and costs. By using more than one modifier,
the analyst can ensure as complete a list as possible isincluded in the CBA. Various modifier ideas can be
found inAdditional Resources.
3. Determine the costs and benefits to be analyzed. Theanalyst can begin listing costs and benefits from
individual research using Google Scholar, Lexis-Nexis
or other online sources for journal and technicalarticles/papers. The papers should give the analyst a
starting point for determining what other information
will be needed. From there, additional items can be
added to the list from HUMINT (talking to experts),
brainstorming, or other idea generating activities.
4. Build a spreadsheet. Using a program like MicrosoftExcel, either build a spreadsheet from scratch or find atemplate online. A Google search for Cost Benefit
filetype:xls should generate a number of already
designed templates. The spreadsheet should include an
area for listing all of the costs followed by all of the
benefits. Each section (cost and benefit) should be auto-
summed to improve accuracy.
5. Determine the number to use for quantifiable data.Through researching costs and numerical benefits, an
analyst can start building the items on the spreadsheet.
If exact numbers are not available, then a range of
costs/benefits should be used. Using Hubbards 90
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Advanced Analytics: Green Team Methods page 12
percent confidence interval (Hubbard, 2010, pp. 55,
103), the analyst should identify the low and high ends
for both costs and benefits. The low and high numbers
should each be listed in its own column to provide a
specific low total and high total for the analysis.
6. Change qualitative data to quantitative. For CBA towork, all data must be in the form of numbers. As such,
any fuzzy items require conversion from ideas to
numbers. Again, using Hubbards ideas for being
creative when approaching items that might be
considered unmeasurable can produce estimates thatare close enough to be able to reduce uncertainty
(Hubbard, 2010, pp. 139-176).
7. Input quantities. All costs and benefits need to have aquantity, or range of quantities, associated with it. Each
item should be listed with what it is and what it costs.
8. Analyze the results. Add all costs together to obtainthe total investment. Then, add all benefits together toget the total benefit. Subtract total investment from total
benefit to get the net value. If the value is positive, you
have a net benefit; if negative, a net cost.
Personal Application
1. Identify a project. The first step was to determine anarea, industry or concept that may not have utilized
CBA in the past. I identified small business cyber
security spending as the area I would investigate.
2. Define terms. To narrow down the items to investigate,I first determined what cost-benefit analysis entailed.
(This is reviewed in the Description section, using the
perspective of one firm.) I defined small business as anorganization with fewer than 50 employees. Cyber
security was defined as any undesirable event that is a
result of an attack against the information system of the
business (Arora, Hall, Pinto, Ramsey, & Telang, 2004,
p. 35).
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3. Identify types of data. I next researched the types ofincidents that are included in cyber security. I found
information pertaining to measuring risk of intrusion,
costs associated with hardware and software solutions,
the maintenance (or update costs) needed for hardware
and software, and the costs associated with monitoring
installed solutions.
To quantify the benefits, I associated the cost of
computers being unusable for an hour/day/week against
the number of incidents prevented because of theinstallation of security devices. To obtain this
information, I spoke with industry experts who advice
and sell security solutions to small businesses. As an
example, a business with a firewall, anti-virus
protection, anti-spam protection and updated
hardware/software can expect next to no intrusions into
their networks. However, by eliminating any one of thesolutions, changes how at-risk the business is to
intrusion.
I decided to use the risk-based analysis because I could
establish different risk levels for different types of
business. I was then able to tailor the analysis based onbusiness risk. I identified five levels that depended on
the type of network and data that a business has on-site.
4. Quantify data. Because the benefit area consisted ofqualitative data, I needed to find a way to measure it.
By using information obtained from experts, journal
1 No network, no client/customer data, no IP, no sensitive documents
2 Networked, with staff data, but no client, IP, or sensitive documents
3 Networked, with staff data plus either client OR IP, no sensitive documents
4 Networked, with either client OR IP AND staff data along with sensitive documents
5 Networked, with client and staff data, IP and sensitive documents
Risk Levels
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Advanced Analytics: Green Team Methods page 14
articles and technical publications, I was able to
identify 90 percent confidence interval for the benefits.
I used the value of prevented incidents formula
developed by Sonnenreich, et al to quantify risk
exposure. The formula I used is:
Risk exposure = ALE = SLE * ARO
SLE = Single loss event
ARO = Annual loss exposure
To determine the cost of a SLE, I used industry dataprovided by the Computer Security Institute and the US
Federal Bureau of Investigation. Again, I used low and
high estimates when calculating the proposed benefit of
prevented incidents.
The other major qualitative measure was the savings to
employee productivity. To determine the cost of loss
productivity, I looked at an average number of incidents
per organization based on the findings of CSI and the
FBI. I then used the number of employees and an
average wage to determine the savings for reducing the
number and length of down-time on a computer
network.
5. Enter costs. The costs associated with any given set ofsecurity answers are more easily constructed. The areas
identified included: Implementation planning, Contract
Value of Prevented Incidents
Cost of single security incident (SLE) Dollars 300 500
Estimated annual rate of occurrence (ARO) Count 12 30Total annual loss exposure (ALE) 3,600 15,000
Monthly Productivity Savings
Employees Count 10 30
Reduced Hours/Month of non-Access Hours 5 10Average Wage Dollars 55 55
Total Monthly Productivity Savings 2,750 16,500
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labor, Internal implementation labor, Training costs,
Opportunity costs, and Capital costs/equipment. The
labor costs are entered for a specific entity. As an
example:
The items entered into the worksheet are then used to
calculate labor and other costs based on the risk level of
the business (the last item on the list).
The risk levels each have associated costs and number
of hours as they relate to each area identified above.
The worksheet is designed to summarize all associated
costs and benefits and then list the suggested hardware
solutions based on the risk level. As an example, the
CBA for Level 5, using the data above computes to:
The list of suggested hardware for the business
includes:
Modem
Worksheet - Enter Values in Right Column
Internal Labor Cost/Hour
IT Staff Cost/Hour Dollars 25.00$
Management Cost/Hour Dollars 65.00$
Other Staff Cost/Hour Dollars 45.00$
Average Wage Dollars 55.00$
External Labor Cost/Hour Dollars 90.00$Expected life span Years 2
Risk Level Number 5
Calculate Total Monthly Benefit Low Est High Est
Monthly Benefit 7,750$ 26,750$
Monthly Cost 6,545$ 13,581$
Total Monthly Benefit 1,205$ 13,169$
Payback (Months) 3 3
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Advanced Analytics: Green Team Methods page 16
Switch Firewall/Anti-spam Backup Document Management Monitoring Dashboard Internet Monitoring
Each risk level has its own hardware suggestions and
CBA analysis.
6. Analyze data. By adding risk analysis to the CBA, I wasable to determine that a business with a low risk forintrusion, such as a mechanic with only one computer
and no client personal data, could invest as little as
$1,300 to secure its data infrastructure and the an
additional $100 a month for on-going maintenance.
Meanwhile, a business with more risk such as a
manufacturer only concerned with protectingintellectual property on its network, can invest from
$9,000 in implementation costs and then $2,000 a
month in on-going costs to $45,000 for implementation
and $6,300 on-going.
Conclusion
The results of the cost-benefit analysis produced results
that could be used to inform decisions; however, it did
not produce results that are estimative. I needed to
include risk analysis in order to obtain enough
information to be able to draw conclusions about the
optimum level a small business should invest.
Additional Resources
http://www.techrepublic.com/downloads/a-project-
managers-costbenefit-analysis/173615
http://www.techrepublic.com/downloads/a-project-managers-costbenefit-analysis/173615http://www.techrepublic.com/downloads/a-project-managers-costbenefit-analysis/173615http://www.techrepublic.com/downloads/a-project-managers-costbenefit-analysis/173615http://www.techrepublic.com/downloads/a-project-managers-costbenefit-analysis/173615 -
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http://www.compliancesforum.com/it-project-cost-
benefit-and-risk-analysis-templates
http://www.infotech.com/sem/costbenefit-analysis-
tool?_kk=cost%20benefit&_kt=821b259e-18e5-49f1-9cb9-df22e94becc6&gclid=CM6g8aDd-
a8CFSWFQAodGEgXDQ
http://www.oit.umn.edu/project-management/project-
toolkit/index.htm
www.pbis.org/common/cms/documents/NewTeam/.../c
ostbenefit.xls
www.dot.state.mn.us/transit/grants/.../Cost_Benefit_W
ksht_4.xls
www.panopticinfo.com/docs/CostBenefitAnalysis.xls
www.projects.ed.ac.uk/.../Full.../ProjectCostBenefitWork
book.xls
www.tc.faa.gov/acf/Cost_Benefit_Template1.xls
http://www.compliancesforum.com/it-project-cost-benefit-and-risk-analysis-templateshttp://www.compliancesforum.com/it-project-cost-benefit-and-risk-analysis-templateshttp://www.infotech.com/sem/costbenefit-analysis-tool?_kk=cost%20benefit&_kt=821b259e-18e5-49f1-9cb9-df22e94becc6&gclid=CM6g8aDd-a8CFSWFQAodGEgXDQhttp://www.infotech.com/sem/costbenefit-analysis-tool?_kk=cost%20benefit&_kt=821b259e-18e5-49f1-9cb9-df22e94becc6&gclid=CM6g8aDd-a8CFSWFQAodGEgXDQhttp://www.infotech.com/sem/costbenefit-analysis-tool?_kk=cost%20benefit&_kt=821b259e-18e5-49f1-9cb9-df22e94becc6&gclid=CM6g8aDd-a8CFSWFQAodGEgXDQhttp://www.infotech.com/sem/costbenefit-analysis-tool?_kk=cost%20benefit&_kt=821b259e-18e5-49f1-9cb9-df22e94becc6&gclid=CM6g8aDd-a8CFSWFQAodGEgXDQhttp://www.oit.umn.edu/project-management/project-toolkit/index.htmhttp://www.oit.umn.edu/project-management/project-toolkit/index.htmhttp://www.pbis.org/common/cms/documents/NewTeam/.../costbenefit.xlshttp://www.pbis.org/common/cms/documents/NewTeam/.../costbenefit.xlshttp://www.dot.state.mn.us/transit/grants/.../Cost_Benefit_Wksht_4.xlshttp://www.dot.state.mn.us/transit/grants/.../Cost_Benefit_Wksht_4.xlshttp://www.panopticinfo.com/docs/CostBenefitAnalysis.xlshttp://www.panopticinfo.com/docs/CostBenefitAnalysis.xlshttp://www.projects.ed.ac.uk/.../Full.../ProjectCostBenefitWorkbook.xlshttp://www.projects.ed.ac.uk/.../Full.../ProjectCostBenefitWorkbook.xlshttp://www.projects.ed.ac.uk/.../Full.../ProjectCostBenefitWorkbook.xlshttp://www.tc.faa.gov/acf/Cost_Benefit_Template1.xlshttp://www.tc.faa.gov/acf/Cost_Benefit_Template1.xlshttp://www.tc.faa.gov/acf/Cost_Benefit_Template1.xlshttp://www.projects.ed.ac.uk/.../Full.../ProjectCostBenefitWorkbook.xlshttp://www.projects.ed.ac.uk/.../Full.../ProjectCostBenefitWorkbook.xlshttp://www.panopticinfo.com/docs/CostBenefitAnalysis.xlshttp://www.dot.state.mn.us/transit/grants/.../Cost_Benefit_Wksht_4.xlshttp://www.dot.state.mn.us/transit/grants/.../Cost_Benefit_Wksht_4.xlshttp://www.pbis.org/common/cms/documents/NewTeam/.../costbenefit.xlshttp://www.pbis.org/common/cms/documents/NewTeam/.../costbenefit.xlshttp://www.oit.umn.edu/project-management/project-toolkit/index.htmhttp://www.oit.umn.edu/project-management/project-toolkit/index.htmhttp://www.infotech.com/sem/costbenefit-analysis-tool?_kk=cost%20benefit&_kt=821b259e-18e5-49f1-9cb9-df22e94becc6&gclid=CM6g8aDd-a8CFSWFQAodGEgXDQhttp://www.infotech.com/sem/costbenefit-analysis-tool?_kk=cost%20benefit&_kt=821b259e-18e5-49f1-9cb9-df22e94becc6&gclid=CM6g8aDd-a8CFSWFQAodGEgXDQhttp://www.infotech.com/sem/costbenefit-analysis-tool?_kk=cost%20benefit&_kt=821b259e-18e5-49f1-9cb9-df22e94becc6&gclid=CM6g8aDd-a8CFSWFQAodGEgXDQhttp://www.infotech.com/sem/costbenefit-analysis-tool?_kk=cost%20benefit&_kt=821b259e-18e5-49f1-9cb9-df22e94becc6&gclid=CM6g8aDd-a8CFSWFQAodGEgXDQhttp://www.compliancesforum.com/it-project-cost-benefit-and-risk-analysis-templateshttp://www.compliancesforum.com/it-project-cost-benefit-and-risk-analysis-templates -
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Chapter 3: Content Analysis
David Krauza
Description
Content analysis is an analytic modifier that uses
systematic, objective, quantitative analysis of message
characteristics (Neuendorf, 2002, p. 1) to determine the
presence of certain words, concepts, themes, phrases,
characters or sentences within text or a set of texts and
quantifies this presence in an objective manner. It entails
a reading of a body of texts, images, and symbolic
material, not necessarily from an authors or users
perspective (Krippendorff, 2004, p. 3).
Content analysis can be divided into two categories ofanalysis, conceptual analysis and relational analysis.
Conceptual analysis is the traditional form of content
analysis. In this method, a concept is chosen and the
analysis involves quantifying and tallying the presence of
the concept in the text(s). Relational analysis starts the
same way as conceptual analysis, with the identification
of a concept. However, relational analysis attempts toidentify semantic relationships in the text. In this form of
content analysis individual concepts do not have
meaning, the results of the relationships among the
concepts reveal the meaning.
Strengths
Content analysis is unobtrusive. When conducting content
analysis, the analyst or researcher does not need to come into
contact with the subject being studied. In fact, the target of the
analysis may never know that they have been the subject of a
study. Given this, there is a very low risk the target will
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change their behavior as is the case with other forms of
observation.
Useful in analyzing trends. Content analysis is useful when
analyzing historical materials. This form of analysis is good
for documenting trends over time.
Harder to trick with denial and deception tactics. Since
content analysis will document trends over time a sudden and
large change in behavior will easily be noticed. To effectively
defeat content analysis the target will have to incorporatedenial and deception tactics in all texts they produce and
maintain the practice over a long period of time.
Weaknesses
May not identify motives. Content analysis is a descriptive
technique. It will produce results that are good at describing
what has happened or what is happening but it may not revealwhy an event occurred or why those involved engaged in the
observed behavior.
Limited availability of data. Like all analytic techniques,
content analysis will be limited by the availability of data. If
the target under analysis does not produce sufficient content to
be analyzed then the technique will have limited benefits.
Vulnerability to bias. Content analysis is subject various forms
of bias. Examples of bias that analysts may engage in include:
not including relevant texts in the analysis and, in the case of
relational content analysis, purposely miscoding text to arrive
at a different meaning.How-To
1. Determine research question. The research question isthe theory or perspective the analyst wishes to examine.
Content analysis research questions differ from
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scientific hypotheses, which is pitted against direct
observational evidence (Krippendorff, 2004, p. 31).
Answers to content analysis questions are made from
inferences drawn from the text.
2. Choose appropriate tools. To effectively performcontent analysis, software tools are necessary (please
see the Additional Resources section for suggestions).
The software can automate the mundane tasks of
tallying word usage and identifying patterns in coded
texts. The analyst must choose the software that best
answers the question/need.3. Obtain necessary texts. There is a wealth of publicly
available texts online. Analysts can use public sources
such as the Security and Exchange Commission, media
archives, and specialized websites, such as Google
Finance or SeekingAlpha.com. The transcripts of
Congressional testimony also offer an excellent source
of content. The advantage that Congressionaltestimony offers is that the speakers must answer
questions truthfully under penalty of perjury. Many
news websites offer an archive of interviews conducted
by their news staff. While a transcript is not always
available (e.g. video of the interview is available on the
website) it still provides another location to acquirecontent. If cost is not a problem there are also paid
websites where content can be found, examples include
Reuters, Bloomberg, and Lexis-Nexis.
4. Analyze texts. This is one of the easier tasks in contentanalysis. Since the software tools will perform the raw
analysis, the analyst will have to stage the data so that
the tool can read the texts and produce output. Itslikely that this step in the process will have to be
repeated several times and new texts are discovered or
anomalies in the data need to be corrected.
5. Interpret results. Once the software tool results areavailable the analyst must attempt to infer meaning
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from the texts. Krippendorff (2004, p. 219)
recommends a statistical analysis of the results to arrive
at an answer to the original research question. Another
way to draw conclusions from the texts is to look at the
report of word usage and draw conclusions from their
usage.
6. Report results. The results of content analysis will beoverwhelming to any decision-maker. It is necessary to
present the results in a user-friendly format, including
creating graphs and charts that can be easily understood
by the intended audience.Personal Application
1. Identify concept. The first step was to choose anindustry to analyze. I chose the technology industry
due to my familiarity with it. Within the industry I
selected Research in Motion (RIM), Apple (AAPL),
Google (GOOG), and Nokia (NOK) to analyze. Ipicked these companies because they are generally
considered to be on different trajectories. AAPL and
GOOG are generally considered to be on the
ascendancy while RIM and NOK are generally
considered to have seen better days. The concept I
wished to investigate was whether public commentary
by company management could provide leading
indicators of operating earnings performance, as
measured by earnings before interest and taxes (EBIT).
2. Determine content analysis method. After determiningwhat concept I wanted to investigate, I needed to
determine what method, conceptual or relational, I
would use for my analysis. I decided to use theconceptual model (see Description section for more
detail) because this model is a straightforward method
and there is a substantial body of research using it.
3. Content analysis software. I examined several differentsoftware packages to perform my analysis. The first
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package I investigated was QDA Minerfrom Provalis
Research. It is a mixed methods qualitative data
analysis package for coding, annotating, retrieving and
analyzing collections of documents. QDA Minercan
also be used to code transcripts, legal documents,
journal articles, and books. QDA Minercoding and
annotating features means that it is a tool that is geared
more towards a relational content analysis. The
package did support the conceptual model through its
text-mining feature, but that required the use of a
dictionary that was not provided with the tool. Giventhe 10-week time frame I had to work with it seemed
implausible to create my own dictionary of financial
indicator terms. This limitation essentially ruled QDA
Minerout from consideration.
Another software package I investigated is called
MaxQDA from VERBI GmbH. MaxQDAsfunctionality is very similar to QDA Miner, however its
text-mining feature is not part of the base product and
requires an additional licensing fee to use. MaxQDA
was eliminated for the same reason as QDA Miner.
The final package I examined was theLinguisticInquiry and Word Counter(LIWC) that was designed
by James Pennebaker
from the University of
Texas. LIWC is based
on Pennebakers
research into the use of
pronouns and functionwords to determine an
authors or speakers
motivation and
intentions. The software
package calculates the
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degree to which different categories are used in source
texts. Pennebakers (2011) theory and software fit
with the conceptual content analysis model I wished to
follow. LIWC is the software I would use for my
analysis.
4. Finding source texts. I collected source texts fromSeeking Alpha. The website maintains transcripts from
investor conference calls. I searched for transcripts
from 2007 to the present (2012). From the website I
was able to extract the text of the call for RIM, AAPL,
GOOG, and NOK and save them into a MS-Wordformatted filed. From Seeking Alpha, I was able to
download 120 transcripts between the four companies.
I had also downloaded the Management Discussion and
Analysis (MDA) section from the companies SEC
annual 10-k filings. However, the language used in the
MDA was very boilerplate and show very little
difference in pronoun usage and I was concerned it wasskewing my results.
5. Execution. After I had was satisfied with the amount oftexts for each company I began my analysis using
LIWC. The output of the LIWC software produced
results counting words for several different categories.
Specifically, LIWC identified word usage commonlyassociated with positive and negative emotion, and uses
of first person singular and plural pronouns. The use of
first person pronouns is significant because according
to Pennebacker an increased usage of first person
singular pronouns (I) is indicative of a depressed
state of mind and a lack of confidence, while first
person plural pronouns (We) is indicative ofconfidence and a feeling of superiority.
With the output of LIWC I graphed the usage of words
for the companies. My graphs were intended to help
assist in the identification of general trends or long-term
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patters. The graphs also had the benefit of making the
data easy to present to viewers of the data, and an
eventual decision-maker.
Once I had the output of LIWC I attempted to correlate
the word usage to the companys EBIT to identify. I
also attempted to run a regression using SPSS on theLIWC results and the companies reported results to see
if a statistical significance existed.
Figure 1: Apple, Inc. Negative Emotion
compared with Operating Profit Margin
Figure 2: Scatter Plot showing the correlation
of Operating Revenue with First Person
Singular (I) Pronouns
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Conclusion
The results of the conceptual content analysis produced
results that are interesting; however, it did not produce
results that are estimative. If the scope of my analysishad been broadened to include more aspects of
relational content analysis, incorporated a larger set of
documents and transcripts, and been conducted using a
longer time period content analysis is likely to get the
analyst closer to a more estimative outcome than I was
able to achieve over the 10-weeks of the project.
Additional Resources
http://secretlifeofpronouns.com/
http://www.liwc.net/
http://www.provalisresearch.com/
http://www.maxqda.com/http://www-
01.ibm.com/software/analytics/spss/products/statistics/
stats-standard/
http://writing.colostate.edu/guides/research/content/
http://academic.csuohio.edu/kneuendorf/content/
http://secretlifeofpronouns.com/http://www.liwc.net/http://www.provalisresearch.com/http://www.maxqda.com/http://www-01.ibm.com/software/analytics/spss/products/statistics/stats-standard/http://www-01.ibm.com/software/analytics/spss/products/statistics/stats-standard/http://www-01.ibm.com/software/analytics/spss/products/statistics/stats-standard/http://writing.colostate.edu/guides/research/content/http://academic.csuohio.edu/kneuendorf/content/http://academic.csuohio.edu/kneuendorf/content/http://academic.csuohio.edu/kneuendorf/content/http://writing.colostate.edu/guides/research/content/http://www-01.ibm.com/software/analytics/spss/products/statistics/stats-standard/http://www-01.ibm.com/software/analytics/spss/products/statistics/stats-standard/http://www-01.ibm.com/software/analytics/spss/products/statistics/stats-standard/http://www.maxqda.com/http://www.provalisresearch.com/http://www.liwc.net/http://secretlifeofpronouns.com/ -
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Chapter 4: Dephi Method
Puru Naidu
Description
Delphi Method is a tool that uses intuitive opinions,
ideas, and thoughts of a group of experts to forecast,
estimate, and decision-making of events and trends. It is
based on the principle that forecasts from a structured
group of individuals are more accurate than those from
unstructured groups. (Rowe and Wright, 2001). The
method can be used to gain consensus on future trends
and projections through a systematic process of
communication and information gathering. (Yousuf,
2007)
Strengths
Flexibility. The biggest strength of Delphi is its flexibility with
participants geographical presence, time, and cost. The
participants can be geographically dispersed while taking part
in the study. The study can be conducted over days or weeks,
and is not time sensitive. The study can be conducted use tools
available on the Internet, and is very cost effective.
Anonymity. The study requires that the participants are
anonymous to other participants. This not only gives equal
opportunity for all participants to voice their ideas and opinions
that may not do so during a live group discussion, but also
prevent participants social status or career status from
influence other members projections.
Simplistic. The method is very simple and easy to comprehend.
The participants can be briefed on the study with just few
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sentences, and they will a good understanding of the purpose
and process of the study.
WeaknessesFacilitator. The method requires a facilitator that constructs,
re-constructs, and analyzes the questionnaires. The facilitators
limited knowledge and biases can influence the forecasting.
Does not work in all circumstances. There is no statistical data
indicating the effectiveness of the Delphi method. It does notnecessarily work for short-range forecasting.
Participant Interaction. The study is only effective when there
are indebt opinions and increased interaction. The study may
require more than two rounds of questionnaires to reach a more
precise forecast.
How-To
1. Identify the topic and resources. Delphi method is aforecasting tool, and hence the topic should align with
its purpose. The organization or individual conducting
this study should identify the facilitator and the channel
of communication that will facilitate the study.
2. Identify the participants. Once the study topic andresources are established, the facilitator needs to look
for participants that have the required expertise in the
topic.
3. Initiate the first round of questionnaire. Send out thefirst round of questionnaire. The questionnaire should
be carefully constructed without any biases and stay inrelevance to the topic of study. It should also include a
basic description of the study.
4. Analyze results. After the first round of questionnaires,the facilitator should analyze all the responses and use
it to reconstruct the second round of questionnaire.
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5. Second round of questionnaire. Send out the secondround of questionnaire. The questionnaire should
include all the views and opinions of all participants
from the first round for other participants to review.
Note: The facilitator can use more than two rounds of
questionnaires until a desired state is reached in the
study.
6. Analyze and Report. Following the last round ofquestionnaires, the facilitator should analyze the
responses and state the findings of the study.
Personal Application
1. Identify the topic and resources. I chose to apply Delphimethod to forecast the outcomes of two events. Premier
League Soccer match between Arsenal and Chelsea,
April 21, 2012, and the Second round off of 2012
French Presidential Elections. My most feasible
resources for the study were Google Docs and schoolemails.
2. Identify the participants. The participants for thePremier League topic were the soccer enthusiasts who
followed soccer regularly, and were once soccer players
them selves. The participants for the French elections
topic were diverse but within college environment. The
participants included students who took political theory
class, students from Western Europe, and students who
followed European news closely. The participants were
talked to individually and made aware of the study.
3. Initiate the first round of questionnaire. Using Googledocs, I constructed the first questionnaire and contacted
the participants through email with the questionnairelinks, and provided them with a time frame to take the
questionnaire. For the soccer study, my forecast
question was Who will win the Premier League match
between Arsenal and Chelsea scheduled on 21 April
2012. And, for the French elections study, my forecast
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question was Who will win the next French
presidential election? Giving the participants all the
possible outcomes of those events to choose from, I
asked them to give their reasons as to why they chose
that. Along with their confidence level in their
predictions.
4. Analyze results. After the first round of questionnaires,I analyzed all the responses and collaborated the
different reasons the participants gave in order of their
predictions. In soccer study, most participants predicted
Arsenal to win because of its good team form and itshome field advantage. There were other participants
who included other factors that would lead Chelsea to
win. In the French elections study, all the participants
chose Hollande to win, with their reasons being the poll
standings and recent news sources that indicated
Hollande to win.
5. Second round of questionnaire. Following the analysisof the first round of questionnaire, I reconstructed the
questionnaire for the second round of questionnaire. I
listed all the views and opinions, and asked the
participants to rate the relevance of the views and
opinions to the outcome of the event.
6.
Analyze and Report. After analyzing the outcomes ofboth the studies, I am inclined to state that Delphi
method doesnt always work, and can also be used with
participants who are not experts in the research topic. In
the soccer study, all participants were experts in the
topic, but failed to predict the correct outcome.
Nevertheless, there was some sort of consensus within
participants with the ratings of the relevancy of theviews and opinions listed in the second round of
questionnaires. In the French elections study, the
participants were not experts in this topic, however they
possessed the abilities for indebt analysis for
forecasting of this event. All the participants predicted
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correct outcome starting from the first questionnaire
and did not change their views.
7. Report results. I presented my analysis and findings toanother Delphi method enthusiast, Mark Burgman, a
professor at the University of Melbourne, Australia.
Conclusion
Delphi Method is a simple forecasting tool that uses
expert opinions and views to forecast the outcome of an
event. Its strengths include its simplicity, costeffectiveness, and the ability of geographically
dispersed participants to take part in the study.
However, in my personal application of this study, I
find that it does not work in all circumstances. Within
the two groups of study, the soccer study group, who
were the experts in topics, was unable to predict the
correct outcome. The French elections study group,despite their lack of expertise in the topic, was able to
predict the right outcome. All qualitative studies state
its effectiveness, but there is no quantitative data to
prove it, and hence needs more research.
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Chapter 5: Game Theory
Shawn Ruminski
Description
In general, game theory is a branch of reasoning commonly
used in economics and political theory. It is best used to
understand the interactions between decision-makers. The
traditional applications of game theory involve modeling
situations in such a way that they represent a simplification of
reality. They are an abstraction we use to understand our
observations and experiences (Osborne, 2000). More
specifically, there are some basic requirements to games.
There are two or more players
There is some choice of action where strategy matters There is at least one outcome, leading to a winner and a
loser
The outcome depends on strategic interaction betweenthe players (Duffy, 2012)
Game theory, at least in the iteration studied for the purposes of
this course, involves two actors with finite choices. Thesechoices have a tangible, measureable consequence. The actors
are rational, meaning that they actively seek to maximize their
payoffs. The game being modeled is most often set up in a
matrix, with the payoffs for each decision laid out in the grid
for each actor. Given the choice between two payoffs, the
actors will pick the higher number.The most common example of game theory is the Prisoners
Dilemma. This is an excellent model which is commonly used
in law enforcement. It shows why two individuals might not
cooperate, even if it appears that it is in their best interest to do
so. The classic description of the Prisoners Dilemma follows:
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Two men are arrested,
but the police do not
possess enough
information for a
conviction. Following
the separation of the two
men, the police offer
both a similar dealif
one testifies against his
partner (confesses), and the other remains silent (denies),the confessor gets a reduced punishment and the
uncooperative man receives the largest sentence. If both
remain silent, both are sentenced to only one month in jail
for a minor charge. If each 'rats out' the other, each receives
a three-month sentence. Each prisoner must choose either
to betray or remain silent; the decision of each is kept quiet.
In this example, the socially preferred course of action is for
both to deny. However, each man is incentivized to confess,
because their individual payoffs increase with confession.
Game theory can be very useful at analyzing and predicting
strategic interactions between actors, but its efficacy is limitedby the accuracy of the model. For this reason, the applications
of game theory are limited. Shubik suggested that while game
theory may be applicable to actual games (such as
backgammon or chess), and may even be useful for
constructing a model to approximate an economic structure
such as a market, it is much harder to consider being able to
trap the subtleties of a family quarrel or an international treatybargaining session (Shubik, 1975). In many situations, actors
are unable to perfectly discern their environment, or their goals
shift over time. These, in particular, are difficult to account for
in game theory. A study done by Green found that game
theoretic experts forecasts were correct only 32 per cent of the
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time, compared with 34 per cent for unaided judgment by
experts and 62 per cent for simulated-interaction (role-playing)
by novices (Green, 2003).
In the proper situations, however, game theory is very useful
for forecasting the interactions between rational actors. Often
times, the simpler games offer more accurate forecasts.
However, the key factor in the effectiveness is rational choice
(Osborne, 2000). Humans do not always act rationally, and this
puts game theory at a significant disadvantage.
Strengths
Focus on the actions of individuals. Rather than being
distracted by temporal elements of the situation, game
theory distills it to the essential, which is the set of
actions possibly taken by either actor.
Should help counter judgmental biases. By examiningthe scenario and identifying the most significant
variables, the analyst will often counter cognitive biases
held regarding the situation as a whole (Green, 2003).
Breaking the scenario into its respective parts interrupts
these biases.
Useful with undisputed assumptions. When the the basic
facts of the environment as translated into the model are
generally agreed upon, game theory tends to be very
successful in exhibiting the qualities of the actual
scenario.
Applicable to a variety of fields. Game theory is provento be effective when applied to military and economics. It
has also been useful, although to a lesser extent, in law,
ethics, sociology, biology, and classic parlor games
(Martin, 1978).
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Weaknesses
Humans do not always act rationally. It is difficult to
game the impact of subjective influences (such as
marketing or advertising in economics)
Quantifying payoffs is difficult. When looking at complex
political models, or other qualitative situations, subtle
differences in the payoffs for actors may have a
significant impact on the optimum strategies for those
actors.
Difficult applications to complex situations. Game theory
is not very effective at modeling complex situations with
many actors. Even in situations with few actors, the
modeling often restricts the number of possible actions
for either actor, since each action much be quantified and
analyzed.
Often constricts the number of options for actors.
Modeling real world environments involves simplifying
the variables. Often this means only analyzing the most
plausible activities for actors. Although in reality actors
could conceivable do any number of different things, in
game theory this is not the case.
How To
1. Isolate the situation to be modeled. The situation mustinclude two or more actors, strategic choices, and some
possible outcomes.
2. Model the situation. The environment must besimplified and distilled into its most relevant variables.
3. Identify actors. For the purposes of this investigation,the number of actors was limited to two.
4. Identify the set of actions available to each actor. Thismay constrict the options available to decision makers.
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5. Assign payoffs to each actor for every possible action.This most often takes the form of a matrix
(simultaneous games) or a game tree (sequential
games).
6. Forecast the probable actions of each actor. This isbased on the rational choices they will make in the
game. This will involve some mathematical calculation
of mixed strategies, such as Nash Equilibrium or
another technique (Osborne, 2000)
Personal Application
1. Isolate the situation to be modeled. I chose to examinespecific situations in a basketball game, from a
coaching standpoint. I am familiar with the game of
basketball, which has many aspects that translate well
to game theoretic analysis. I specifically identified both
dealing with foul trouble, and an end of game scenario
where a team is down two points near the end ofregulation with the ball.
2. Model the situation. For the situation of foul trouble,the application of game theory was much more difficult
than for the second situation. This was because it was
difficult to model the actions of the coach versus the
actions of the player for foul trouble. In the second
scenario, I simplified the end of the game to two actors,
with two possible actions each.
3. Identify actors. For the first situation, the actor was thecoach, with the second actor being the teams starter or
bench player. In the second situation, the actors were
the two coaches involved in the game.
4. Identify the set of actions available to each actor. Forthe first situation, the coachs actions are benching orplaying a starter in foul trouble. The players actions
were their performance on the court. This was
determined by a statistic called Wins Produced per 48
minutes (WP48). In the second situation, the coach of
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the team that has the lead, the defending coach, could
choose to defend a two point shot or a three point shot.
The coach of the team that is losing, the offensive
coach, can choose either to shoot a two point shot or a
three point shot.
5. Assign payoffs to each actor for every possible action.For the first situation, payoffs were assigned based on
the calculated probability of fouling out, coupled with
the WP48 statistic. In the second situation, payoffs for
shooting or defending each shot were based on shooting
percentages from this past year in the NBA, and studiesregarding open shooting percentages and the effect of
good defense on shooting percentages.
6. Forecast the probable actions of each actor. For thefirst situation, the coach should let his starters play, in
spite of foul trouble. However, I provided data that this
is often not the case. In the second situation, the
analysis shows that it is likely in the best interests of thelosing team to shoot the three almost all the time. As
long as the defending (winning) team guards the three
pointer less
than about
80% of the
time, thelosing team
should seek
to end the
game in
regulation
every time.
Similarly,the team that is ahead should fear the three pointer
much more than overtime. As long as the team that is
losing shoots the three at least a third of the time, the
defending team should always defend the three.
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Conclusion
Game theory is an excellent way to evaluate actors most
effective strategies. However, an effective application involvesa situation with accurate modeling, including the preciseevaluation of payoffs, is required in order to get the most out ofgame theory as an intelligence methodology. Furthermore, it isimportant to assess the target actors evaluation of payoffs,rather than applying an arbitrary evaluation. However, givenapplicable situations and accurate models, game theory lendsitself well to intelligence analysis and forecasting.
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Chapter 6: Comparative News Frame
Analysis
Emily Slegel
Description
Comparative News Frame Analysis is an analytic modifier that
uses quantitative and qualitative analysis of words in texts to
understand how one specific frame is being presented acrossnewspapers and media outlets across cultures and countries by
comparing analyzed frames. Frames are how an individual
cognitively comprehends and files events, and the news can
provide a pseudo-environment for the readers, thus framing
the event for the public. The frames adopted by media to cover
terrorism and the ones adopted by governments to report and
respond to have the power to influence the societys perception
of terrorist activity. Comparative News Frame Analysis is used
to determine one specific frame thus understanding the
perception of terrorist activity, for example, within that country
or culture comparing it to other frames to understand the
current situation. Comparative News Frame Analysis can be
applied to various issues and events in history, from crises tothe adoption of governmental policies. The technique is
reliable up to a certain point, but is limited solely based on the
understanding of the topic and technique. The method is fairly
flexible and useful even with a small, but sufficient, amount of
data.
Within Comparative News Frame Analysis, there are a varietyof qualitative and quantitative techniques within which to
compare frames in newspapers. One technique includes
discourse analysis, which seeks to understand links between
texts by identifying particular frames. This is done by reading
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the text several times and marking certain contextual items
present. A quantitative technique for comparative news frame
analysis is centering resonance analysis. This type of analysis
calculates the words influence within texts, using their
position in the texts structure of words. Once the influential
words scores are calculated, these results indicate the authors
intentional acts regarding word choice and message meaning.
The analyst then can draw conclusions from these messages to
determine the frame.
Strengths
Can use a small data set to draw conclusions. Comparative
News Frame analysis does not require a large data set in order
to draw conclusions. The method is also very useful with
textual data. There are no limits to the amount of news sources
being examined.
Method is easily understood. Due to previous literature andacademic research the method is well documented and is easy
to understand.
Can be used in variety of languages. Native speakers in non-
English languages will be able to use this technique.
Any news source can be analyzed. Any topic can be analyzed
using Comparative News Frame Analysis.
The results can be easily communicated to decision makers.
Using quantitative techniques, it is an easy method to complete
with aid of software.
Weaknesses
Can only examine one frame/event at a time. The method does
not allow for more than one event to be examined at a time.
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For more robust results a larger amount of data is required.
Some articles do not contain relevant textual items to
examine/analyze. If few articles are available more robust
results may not be possible. It may be challenging to find
articles on one frame from different areas.
Conclusions require experienced and knowledge of analysts.
Once the data is produced, the analyst must draw conclusions
on the frames based upon: experience, knowledge and previous
literature
Susceptible to denial and deception. The analysis relies on
what is published in the media, therefore denial and deceptions
tactics can skew the results.
How-To
1. Pick a problem or issue to examine that is able to seenacross cultures or countries.
2. Research writings on the problem or issue that comefrom that region, country, or culture including
examining local newspaper articles, national newspaper
articles and blog sources.
3. Pick articles on the topic.4. Determine qualitative, quantitative or mix techniques
for the analysis:
a. Qualitative TechniquesDiscourse Analysis:Articles are read over to identify frames, which
include conflict, human interests, economic
consequences, morality and responsibility.
These frames are identified by symbols that
carry specific attitudes and positions, whichinclude: metaphors, exemplars, catch phrases,
depictions, visual images and appeals to
principal. Examine the percentages of favorable
terms, neutral terms and unfavorable terms.
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b. Quantitative TechniqueCentering ResonanceAnalysis: I used Crawdad, which is software
based on the concept of CRA. CRA analyzes
text by creating word networks of nouns and
noun phrases that represent main concepts, their
influence and their relationships. Simply input
the .txt file into the program and convert it to
Crawdad-specific format (.cra). From there
the software completes all the calculations on
the desired articles individually. Crawdad
calculates two scores for each article, theinfluence and resonance scores. The higher the
scores, the more influences and more
betweenness centrality the word has within that
article. Influence scores range from 0 to 1. A
score of 0.05 or higher is considered significant
by leading researchers in the area, and a
score above 0.1 is considered very significant.5. Once results are achieved, determine the trends and
draw conclusions.
6. Can make Excel graphs and other methods to visualizethe results to decision maker.
Personal Application
1. Identify concept. The first step was to choose a terroristattack/event. I had to choose an event that had each
article would be long enough in terms of words to
compare, as well as had a variety of international news
coverage. I chose the Madrid Train Bombing because
of the international coverage that it had, as well as the
articles had enough words to use for comparison. Thechallenge was that there was a lot of repetition of a
single article in many news sources, so finding an
original source of news coverage on the attack was a
challenge. By using Google News Search Engine and
LexusNexus I was only able to find 6 news articles that
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were locally written. The concept I wished to
investigate was if the Madrid Train Bombing was
viewed differently in different countries and regions to
understand the perception of terrorism in those
countries.
2. Determine Comparative News Frame Analysis. Once Ipicked the event, I started researching the variety of
news frame analysis available to determine the
appropriate frame analysis method to use. I began
investigating strategic frame analysis, which analyzes
news by looking at the subtle selection of certainaspects of an issue in order to frame the event. This
would not work for my topic, for I wanted to analyze
different countries or regions perception of the
Madrid Train Bombing by analyzing the frames in the
news. Then I discovered a variant of news frame
analysis that is Comparative News Frame Analysis,
which looks at one particular topic and compares theframes presented by analyzed news articles in various
areas of the world. I decided to use this method for
there is a large body of research using this type of
analysis to research similar topics.
3. Research Frames and Framing. After determining mymethod to understand how the Madrid Train Bombingis viewed in different countries, I started researching
what frames are and what they do and can do. This was
a large and lengthy process due to the vast amount of
information available. There are also different academic
views of frames and framing, for example psychology
and sociology have two different views of frames and
framing and I had to determine which definition offrames I would like to use when applying Comparative
News Frame Analysis. It is important to note that an
analyst would need to have strong background
knowledge of frames and framing to fully understand
the results of the analysis. I read the book Psychology
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of Prejudice to understand the topic of prejudice and
stereotyping along with other articles on frames and
framing.
4. Choosing Techniques. There are a variety of methods toconduct comparative news frame analysis, but based
upon previous research, which focused on news
coverage of other terrorist events, I followed the same
path of using discourse analysis, a qualitative
technique, and centering resonance analysis, a
quantitative technique.
5. Execution. When applying discourse analysis to my sixnewspaper articles, this technique appeared to have thepotential to be easily flawed and did not prove to be an
effective way to analyze the newspapers. I have
concluded that for the qualitative analysis, one would
need a very good knowledge of identifying textual
items including metaphors, exemplars, catch phrases
and depictions. Besides being able to simply identifythese textual items the analyst would also have to know
what it means. This could easily cause issues to the
everyday analyst using this one method of analysis.
Also I did note that some articles didnt contain some of
the textual items to examine/analyze, which I figured
was going to happen but nonetheless was a challenge.
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I chose centering resonance analysis as the quantitative
technique, for the other types of quantitative analysis used in
other papers seemed to focus on the content itself, not the
relationships that these words have in the articles, which helps
the analyst understand the frame of the newspaper article. This
was seen in a study that also studied a particular act of
terrorism, comparing US to UK newspapers. I used Centering
Resonance Software by Crawdad. The software was easy to
use, though the analyst must draw the conclusions, which can
be subjected because it is based upon experience, knowledge
and previous experience. Crawdad also made it very easy to
visually understand the differences between the newspapers
when looking at the links and relationships between the words.
After reading all the results of the different articles, I made avery quick and simple graph, which enabled the results to be
easily understood.
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ConclusionThe results of the quantitative and qualitative techniques are
replicable, but it allows for the analysts to introduce bias into
the conclusion. Comparative News Frame Analysis can help an
analyst further in his or her research in an area or topic but its
results do not produce an intelligence estimate itself. Also, the
method was easy to complete with aid of the software and canhelp an analyst communicate to the decision maker because of
the low technical word usage and is theoretically easy to
understand. Finally, I was able to answer my question on how
different countries perceive terrorism but I would need more
data to have more robust results.
Further Information
Crawdad Technologies, L. (2005). Crawdad Text Analysis
System version 1.2. Chandler, AZ.
http://www.crawdadtech.com/
IYENGAR, S., & SIMON, A. (1993). News coverage of the
gulf crisis and public opinion a study of agenda-setting,
priming, and framing. Communication Research, 20(3), 365-
383. Retrieved from
http://crx.sagepub.com/content/20/3/365.short
KOENIG, T. (2006). Compounding mixed-methods problems
in frame analysis through comparative research. Qualitative
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Research, 6(61), 6176. Retrieved from
http://qrj.sagepub.com/content/6/1/61.full.pdf
Papacharissi, Z., & Oliveira, M. (2008). News frames
terrorism: A comparative analysis of frames employed interrorism coverage in u.s. and u.k. newspapers. The
International Journal of Press/Politics , 13(1), 52-74 . Retrieved
from http://hij.sagepub.com/content/13/1/52.full.pdf+html
Zanna, M. P., & Olson, J. M. (1994). The psychology of
prejudice. Lawrence Erlbaum.
ZHANG, J., & FAHMY, S. (2009). Colored revolutions incolored lenses: A comparative analysis of u.s. and russian press
coverage of political movements in ukraine, belarus, and
uzbekistan. International Journal of Communication, 3, 517-
539. Retrieved from
http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=
web&cd=10&sqi=2&ved=0CH4QFjAJ&url=http://ijoc.org/ojs/
index.php/ijoc/article/download/253/327&ei=cACHT-
x6iODRAfHpwY0H&usg=AFQjCNGIxbLtYMSJLPBImON6
acbcPmoCEQ&sig2=IQ2IZouGQJjAY0pPwduprw
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Bibliography
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