NSA Your Secret Follower

Rohit kumar

Nov 2013

Objective, Timeframe and Source of Data

Objective: Capitalizing, qualifying and quantifying the tweets about NSA on Twitter

Time frame : October 2013 to November 2013

Geography: Tweets from across the world were considered for the data collection

Language: Tweets which are only in English were selected after filtering other national languages

Note :

• For the analysis, open source Social Media monitoring tool Trackur was used.

• This analysis is indicative and provides directional guidance on how NSA is perceived across the

world.

• The data used for analysis solely dependent on the tool used, volume of the data captures and

timeframe considered for the study and human intervention to ensure data has consistency and

credibility to derive inferences

Source: Trackur – http://www.trackur.com/

How Noise was excluded from Data

1. Some tweets were in language other than English which were not considered for data analysis

Example: Documentos da NSA so distribudos como

segurana.https://twitter.com/BrendaGwen_/statuses/389833378029395968

2. Few Tweets were repeated multiple times which were directing us to the same source by the same

user hence they were not considered for data analysis

3. Few profiles from the data were either suspended/ page doesn’t exist which are represented below:

A) Example: The National Security Agency is gathering email...

https://twitter.com/pRaTiK_wow/statuses/389944722925817856

B) Example: NSA Discloses Cellphone Location Tracking Tests:..

https://twitter.com/TriumphCISO/statuses/385795119053430786

Data Analysis :Approach and execution

Data Collation and Cleansing

Negative Neutral Positive Total

Initial data from the tool 155 603 24 782

Final data after cleansing 168 489 18 675

155

603

24

168

489

18

Negative Neutral Positive

Data Cleansing

Initial data from the tool Final data after cleansing

782

675

Intial data from the tool Final data after cleansing

Total Tweets

• After reading through the tweets we could infer that there are 107 tweets which can be considered

as null/invalid based on the language, repetitive tweets, inactive links and suspended accounts.

• We have listed all these invalid tweets in our reference sheet with the tab name as “Tweets –107”

Sentiments of the Overall Posts

• The overall sentiment of posts were neutral considering the fact that they was more viral in terms of

what and how NSA has been carrying out their operations, the opinions of the public are also captured

along with the categories which are shared in the proceeding slides in detail

Total Number of posts N=675

Negative, 25%

Neutral, 72%

Positive, 3%

168

489

18

Negative Neutral Positive

Overall Posts by Category

• Most of the tweets were primarily having mentions about Obama/Govt. which has a direct correlation to

NSA in the tweets that were gathered followed by the discontent by the companies which have the data

of the customers which were accessed by NSA without their approval

Total Number of posts N=675

55

15

21

18

566

0 100 200 300 400 500 600

Companies

Countries

Edward Snowden

NSA Employees

Obama/Govt

Qualitative Sentiment Analysis

• Most of the tweets were centered around the way in which NSA/Obama administration has handled the

entire situation, it has received most of its tweets under the sentiment as "Neutral" considering the

articles which were published by the various news corporation for the knowledge of the pubic.

Total Number of posts N=675

Companies Countries Edward Snowden NSA Employees Obama/Govt

8

11

4

7

138

47

4

15

11

412

216

Positive

Neutral

Negative

Snapshots of TweetsExamples of Twitter - sentiments

Overview #NSA Tweets

• The National Security Agency of the United States (NSA) spied 35 phone calls from world leaders

• The National Security Agency recorded information about more than 124 billion phone calls in one

month

• The National Security Agency has been harvesting millions of e-mail addresses from contact lists of

users of sites such as Facebook, Gmail, Hotmail and Yahoo.

• French Condemn Surveillance by N.S.A.

• The NSA Hacked Former Mexican President Felipe Calderon’s Email While He Was In Office

• The National Security Agency, the controversial U.S. surveillance agency, has had a tough few weeks,

as new allegations from leaked documents have angered more allies.

• Edward Snowden: US would have buried NSA warnings forever

• Snowden claims Russia, China did not get NSA documents

• National Security Agency has had limited success in cracking Tor communications

• Government Shutdown Slows NSA Surveillance Reform Efforts:

• NSA’s vast new Utah data hub suffering from ‘meltdowns’ – report

• White House confirms National Security Agency (NSA) chief to step down

Introduction

Mean while this is what White House tweeted,

there is no link to view the Photo in this tweet !

How other Countries reacted !

How NSA is used by its own employees

NSA Website was Attacked

NSA — Positive tweets

White House press secretary Jay Carney

confirmed that National Security Agency

Director Gen. Keith Alexander would step down

early next year but downplayed suggestions his

departure had anything to do with recent

damaging leaks from Edward Snowden.

NSA — Neutral tweets

NSA — Negative (Sarcasm) tweets

NSA — Negative tweets

Manual intervention - Changed the sentiment from “Positive” to “Negative/ Neutral” –

Positive to Negative Positive to Neutral

Positive to Negative Positive to Neutral

Conclusion

Neutral

Based on the analysis carried out on the data we have derived the following:

• Most of the articles had their reference to the twitter account of the news corporation which

twitter users (individuals) have leveraged for retweeting so the sentiment remains to be neutral

• There are few instances in which the tool has captured the tone in a way which the user never

intended the tweet to be so we had to change the sentiments, the examples for which were

already in the earlier slides

• Few of the twitter users have dared to tweet about NSA directly in a tone which was Negative

and few have taken an alternate route of using Sarcasm but most of them refrained from

commenting hence we have most of Tweets on an Neutral Tone from the data .

In conclusion we infer that the overall tweets are mostly having a “neutral "sentiment towards NSA