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


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


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


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


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)


The tool analyses multiple sources

• The Milan City prototype crawles:

•Twitter

•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


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.


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!»


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


The ideal tool integrates all these components


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:():(+).


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.


DEMO


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


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%


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


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


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»

Business

ENTER2011/IFITT - Case Study of Milan City