ENTER2011/IFITT - Case Study of Milan City
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Transcript of ENTER2011/IFITT - Case Study of Milan City
Web intelligence tool (Wispo): the case of Milan City
Web Intelligence Tool (Wispo)The case study of Milan City
Lugano, Jan. 27th 2011
Web intelligence tool (Wispo): the case of Milan City
A strategy to manage a brand’s online reputation has become a must
Measure Understand ActStrategy
Managerial issues
• Collect information from the Web
• Understand:
Where people exchange opinions on a brand
How much people talk about a brand
What people say about a brand
• Analyze data
• Understand what is the general sentiment about a brand
• Identify the positives and negatives of a brand
• Improve a brand’s online reputation with targeted marketing initiatives
• Act both online and offline to communicate the positives and mitigate the negatives
Web intelligence tool (Wispo): the case of Milan City
The project with Milan City
We have developed a methodology and a tool to analyze the online reputation of Milan city as a tourist destination
• A tool supports the collection and analysis of large volumes of data
• Automated analyses are cheaper and can be performed continually
• Data visualization techniques can help understanding
• A tool combines the traditional top down approach (similar to traditional questionnaires) with a bottom up approach that highlights the critical features of a brand based on online conversations (unbiased)
Advantages of an automated approach
Web intelligence tool (Wispo): the case of Milan City
The Digital Reputation Lab at Politecnico di Milano
• To promote research on the open issues in the semantic analysis and exploitation of Web 2.0 content
• To evaluate existing technologies (both closed and open)
• To develop new components that fill a technological gap
Objectives of the Lab• COGITO
• Radian6
• Buzzmetrics
• Extrapola
• Asomo
• Open Source technologies
• …
Market technologies
• Crawler
• Cleaner
• Stemmer
• Semantic engine
• Analysis components
• Mash-up dashboard
• Data quality components
Lab technologies
50+ international publications
8 FTE in the lab
Web intelligence tool (Wispo): the case of Milan City
Innovative features of the Web Intelligence Tool (WITty)
Single integrated semantic network for all analyses (disambiguation, syntax, semantics, sentiment)
Accurate and dependable evaluation of sentiment
Semantic analysis of conversation volumes
Identification and analysis of influencers
Open mashup interface (proprietary and Web-based components)
Web intelligence tool (Wispo): the case of Milan City
The tool analyses multiple sources
• The Milan City prototype crawles:
•TripAdvisor
•Lonely Planet
•Facebook (from Q4 2010)
• We collect data automatically and continuously
• Analyses on Milan City are based on a data set of over 1 million posts
Web intelligence tool (Wispo): the case of Milan City
Posts must be “translated”
• We have developed a cleaner that translates the Web 2.0 “lingo” into “English”. The cleaner handles:
Slang
Abbreviations
Web lingo
Spelling checker
i hope my haters didnt have too much money on me not coming back to london?? lol as im leaving and coming home in 2 more sleeps :-) x
Examples
ahhhh nice. I was in milan this weekend. Was funnnn!
r u coming to madrid? if so let me know, i wanna meet with u =)@AyuWorld @crea_spain yea, i got an invitation to go to Spain, not sure yet^^
i hope my haters did not have too much money on me not coming back to london? Laughing out loud as i am leaving and coming home in 2 more sleeps.
ah nice. I was in milan this weekend. Was fun!
are you coming to madrid? if so let me know, i want to meet with you yeah, i got an invitation to go to Spain, not sure yet.
Web intelligence tool (Wispo): the case of Milan City
The analysis of the volumes of conversations must be semantic
• Words change their meaning radically depending on context
• We have developed a semantic disambiguation tool customized for the tourism sector
«I have just arrived in Milan. Here food is great!»
Posts including the keyword “Milan” *
* On a total of 337.703 tweet from 28/5/2010 to 20/10/2010
100%
83%
14%
3%
Total AC Milan
Milan city
Other(Milan Kundera, Alyssa Milano, Milano cookies…)
«I have just read great news about Alyssa Milan.»
«I love Milan Kundera…»
«Beating AC Milan is going to be a challenge!»
Web intelligence tool (Wispo): the case of Milan City
Identifying relevant posts is not enough, posts must be interpreted and their sentiment must be scored
• Adjectives can carry either a positive or a negative sentiment depending on context (e.g. a small cell phone vs. a small hotel room)
• The evaluation of sentiment requires a semantic analyzer: identifying individual words with sentiment (e.g. wonderful) is significantly error prone
• Sentiment cannot be always evaluated correctly
• Our tool recognizes whether sentiment can or cannot be evaluated correctly with a recall above 80% and a precision above 90%
When I wake up I'll be in Milan! Great wine and great fashion lies ahead!
WHY is it so COLD in Madrid? Don’t like at all
I'm at Milan Linate International Airport w/2 others.
Examples
Web intelligence tool (Wispo): the case of Milan City
The ideal tool integrates all these components
Web intelligence tool (Wispo): the case of Milan City
Sample output of our semantic engine
HAVE TO MUCH FUN OUT IN MILAN LAST NIGHT. THE FOOD HERE BE NOT AS GOOD AS I THINK IT WOULD BE. LOVE MILAN. GALLO GET MUCH LOVE HERE. BE GREAT. I BE IN PARIS RIGHT NOW AND I KNOW I SEE THE WEATHER BE LIKE 80 RIGHT NOW. I WANT TO BE HOME IN THE O SO BAD.
Positive sentiment
Positive sentiment
Negative sentiment
Branding
Categorization
***BRAND:MILAN:17***.MESSAGE WRITER:57:():(/).LIKE:121:():(/).MILAN:17:(|>###BRAND:1950):(+).
***BRAND:MILAN:17***.MESSAGE WRITER:57:():(/).VERB_VOID:19:():(/).NIGHT:471:(|>EVENING:1707>NIGHT AND MUSIC:1661>###CLIENT_DOMAIN:1655):(/).BE:5:():(/).LAST:360:():(/).
***BRAND:MILAN:17***.MILAN:17:(|>###BRAND:1950):(/).VERB_VOID:19:():(/).FOOD:18:(|>FOOD AND DRINK:1663>###CLIENT_DOMAIN:1655):(/).NOT BE:670:():(/).TASTY:16:(|>FOOD AND DRINK:1663>###CLIENT_DOMAIN:1655):(-).
***BRAND:MILAN:17***.MESSAGE WRITER:57:():(/).LIKE:121:():(/).MILAN:17:(|>###BRAND:1950):(+).
***BRAND:MILAN:17***.MILAN:17:(|>###BRAND:1950):(/).VERB_VOID:19:():(/).PERSON:61:():(/).GET:103:():(/).LOVE:277:():(+).
Web intelligence tool (Wispo): the case of Milan City
The tool can identify the sentiment of posts where the brand is not cited explicitly
The tool provides more conservative, but correct information:
•Positive sentiment 75% (have fun in Milan, like Milan, get love in Milan)
•Negative sentiment 25% (food not as good) – not explicitly referred to Milan, it depends on what “here” means.
Web intelligence tool (Wispo): the case of Milan City
DEMO
Web intelligence tool (Wispo): the case of Milan City
Travel related conversations are distributed in 5 dimensions of a city brand model
Distribution of conversations (Twitter, TripAdvisor, Lonely Planet; Q3 2010)
Data: 113.000 posts travel-related (London, Milan, Madrid and Berlin)
30%
13% 6%
31%20%
Presence:It refers to the visibility of a city and its contribution to global knowledge and trends. It includes dimensions such as Events & Sport
Prerequisites: It refers to basic services such as: accommodation, transports, fares.It includes dimensions such as Services & Transport, Fares & Ticket
People: It refers to the character of citizens, their open mindedness, their cultural biases. It includes dimensions such as Life &Entertainment
Place:It refers to the physical aspect of a city, including beauty, cleandiness, climate. It includes dimensions such as Weather &Environmental, Food & Drink
Pulse:It refers to the city life style, inense and vibrant, to social and cultural events. It includes dimensions such as : Arts & Culture, Night & Music, Fashion & Shopping
Web intelligence tool (Wispo): the case of Milan City
London is a benchmark for all dimensions with the exception of “presence”
Percent volumes of converstations (Twitter, TripAdvisor, Lonely Planet; Q3 2010)
Base: 113 mila messaggi
London
Madrid
Milan
PLACE
PEOPLE
PULSE
PRESENCE
-60% Media +30% +60%-90%-120%
Milan is positioned close to London regarding the pulse dimension of the city brand model, mainly due to fashion events in september
+90%
PRE-REQUISITES
Berlin
+180%+150%+120%-30%
Web intelligence tool (Wispo): the case of Milan City
Data are interpreted with a brand reputation model that aggregates and weighs information
Domain keywords of Milan City
Milan
Services & Transport Fares &
TicketsLife & Entertainment
Arts & Culture
Night & Music
Fashion & Shopping
Events & Sport
Weather & Environmental
Food & Drink
Apartment
Accommodation
Parking
Classes
University/ CollegeSummer school
Internet Wi-FiRetail
Information point Website
ResidenceCamping
Hotel Hostel
Online reservationCheck in/out
Star ShuttleMapStudent
Course
Train
Tube/ underground
BusTram
TaxiFlightTravel
Station
Airport
City center Trip/journeyCycling
Bike sharing
DelayTour
Budget
Card
Last minute
Price/chargeTicket machineBooking
WeekendPeople
Safety
Photo Movie
Dance
Market
FriendNetworking
Meeting
Walking
Driving
Wallet
Film center
Film festival
Premiere
Art fair & marketCollectors
Photography
Design Street art
GalleryMuseum
PerformancesProgramme
Artist Architecture
MonumentChurch/ cathedral
HistoricalFriday
Saturday
Theatre
ClubParty
Concert
Exhibition Jazz
FestivalMusical/opera
Trend
Fashion district
Shopping
StyleLuxury
Model GlamourSale
Window Fun
Shopping center
Expo
Show
Sponsor
Football/ soccer
Association
GamePlayClub
Champion
Betting
Olympics
Cold
RainSun
Pollution
Square
Park
Stadium
Street
Historical shops
WindySnow
CrossDrive
Traffic
Place World
Bar
Restaurant
Breakfast
Dinner
Lunch/ meal
Eating/ dining
Coffee/ teaCocktail
WineBeer
ItalianFishJapanese
Indian
Pizza
Transport
Eco friendly
Shop
PrerequisitesPeople
Presence
Place
Pulse
Web intelligence tool (Wispo): the case of Milan City
Project results
• Over three million messages have been collected on 4 cities from 4 sources. Content has
been cleaned, analyzed and stored. The share of messages expressing sentiment has been
extracted from the mass of raw data and evaluated. Branding initiatives have been launched
accordingly.
• 5% of messages were found to have travel related sentiment
• London is a benchmark on all structural dimensions (Pre-requisites, Place, People); Milano
has more volumes on Presence and Pulse
• Milan is going to act on its own influencers to have a flow of messages that are explicitly
referred to the city and can increase the city’s visibility, with a continuous effort to implement
enabling technologies and design enabling services to create an online presence that can have
an impact
Web intelligence tool (Wispo): the case of Milan City
Strategic use of the tool
• The tool is live at the Directorate of tourism of Milan City Hall
• The tool is used as part of the excutive information system
• The tool is also used to provide management consulting services
to the Directorate of tourism
• We are working on the idea of using the tool to assemble/edit
user-generated content
• We are working on the idea of using the tool to build a sentiment-
filtered «daily»