CULTURAL ANALSYS OF CRAWLED CAMPAIGNS

USE CASES:US elections - Rock am Ring

Why cultural analysis

– there are significant differences in the general characteristics of the Twitter network in different countries,

– And more generally, in the different social media,– differences should be taken into account in

designing crawling and preservation strategies,

US Elections 2012 Crawl

• We crawled tweets on the US elections 2012 using some target key words (e.g., obama, romney, republican,…) from 1st to 11th November 2012 to

• Let’s analyze them from a language perspective

Languages distribution exhibits a power-law

Language’s usage are power distributed

• What does it means here “a power law”– By analyzing the figure, the largest majority of

engaged users are tweeting in the same language “english” (exponentially more than tweets in othe languages)

– Ok, it is not suprising!

What about user engagement

• Do people engage in the same way whatever the language?

• How can we measure user engagement ?• There is many ways, one simple is:– The average number of tweets by user in a specific

language.

User engagement

en es de it in ar pt fr pl ko nl ja tr sv tl undda vi lt fa zh ru no is th el hu id ur iw bg ne ta hy hi bn si my ml km bo pa te ka kn gu lo0

2

4

6

8

10

12

14

16

18

20

#users/#tweets

Chinese and Iranian are highly Interested by US elections!!6127 tweets in farsi done by 430 users5282 tweets in 282 in Chinese

Language-based user engagement

Farsi and Mandarin, the us election’s languages.

• User engagement is higher in Farsi or in Mandarin than in English– It means, there is fewer people tweeting in Farsi

or Mandarin, but, people when considering people tweeting about the uselection, then people tweeting in Farsi or in Mandarin tweets in average more about uselection than people tweeting in english.

– It reveals an important cultural information taken out from the social media. Us elections get a great audience from farsi (Iran) speakers and mandarin (Chinese).

Rock am Ring campain

• Let’s do the same analysis on Rock am Ring event, by again crawling tweets from a set of key words related to the event

• But this time, let’s analyze countries• The country information can be in majority of

cases extracted from the user profiles.

Countries distributions

German

y

United

Brazil

Japan

Spain

Indonesia

Chile

Argentina

Mexico India

France

Venezu

ela

Canad

aRussi

a

Netherl

ands

Norway

ColombiaIta

ly

Turke

y

Australi

a

Belgium

Nigeria

Switz

erlan

dSo

uth

Poland

Austria

Thail

and

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

#tweets#users

Geo-location activity

What do we observe?

• Germany, United States and Brazil are the countries more engaged on Twitter for the event

User engagement ?

German

y

UnitedBraz

ilJap

anSp

ain

IndonesiaChile

Argentina

Mexico India

France

Venezu

ela

Canad

aRussi

a

Netherl

ands

Norway

ColombiaIta

ly

Turke

y

Australi

a

Belgium

Nigeria

Switz

erlan

dSo

uth

Poland

Austria

Thail

and

Portuga

l0

1

2

3

4

5

6

#tweets/#users

Geo-location user engagement

User engagement

• This time, user engagement analysis seems to tell us that users located in “Thailand” a very engaged with “Rock am Ring”

• Be careful, the sample is too small (40 tweets) to assess any statistical significance about this observation!

• Try to collect more Tweets.