TWITTER RESEARCH:
STATE OF THE ART AND
OPEN CHALLENGES
Katrin Weller
@kwelle
katrin.weller@gesis.org
1
Präsentation im DAS...
Introduction to TwitterPart 1
Twitter: A Short Introduction
3
Jack Dorsey (2000): “twttr sketch”. http://www.flickr.com/photos/jackdorsey/182613360/
Twitter: A Short Introduction
4
Twitter: A Short Introduction
5
Tweet = 140 characters
Twitter: A Short Introduction
6
Followers and Followees
Twitter: A Short Introduction
7
Twitter: A Short Introduction
8
Twitter Terminology
9
Retweet
(RT, via)
Kooti, F., Yang, H., Cha, M., Gummadi, K.P. & Mason, W.A. (2012). The Emergence of...
Twitter Terminology
10
@message
(≠ direct message)
Twitter Terminology
11
#
Hashtags
Hashtags
12
 Memes
 Conventions
 Trends
 Influence
 #becareful!!!
March 19, 2012
Twitter: Numbers
13
 Founded in 2006 (independent Plattform
since 2007)
 March 2012: 140 million active users and
340 mi...
Twitter vs. Facebook
14
In Germany
Facebook: 72.1% (of Internet users)
Twitter: 10.5% (of Internet users)
German Social Me...
Twitter: Trivia
15
 Twitter users with most followers?
 Trends 2012: olympics, US election
 Most retweeted:
https://201...
Twitter: Popular Users
16
March,2013,http://twittercounter.com/pages/100
Twitter Tools
17
Twitter Tools
18
19
Twitter ResearchPart 2
Development of Twitter Research
21
0
200
400
600
800
1000
1200
2007 2008 2009 2010 2011 2012
Scopus WoS SSCI Scopus: Socia...
Twitter vs. Facebook
22
0
200
400
600
800
1000
1200
1400
2007 2008 2009 2010 2011 2012
Scopus: Twitter Scopus: Facebook
Scopus: Publications from 70 countries
23
United States; 958
United Kingdom; 174
Japan; 166China; 140Germany; 115
Australi...
Scopus: Publications by Discipline
24
1621
519
375
291
284
178
115
98
48
41
0 200 400 600 800 1000 1200 1400 1600 1800
Com...
Why Study Twitter?
25
pointless babble?
Early Twitter Research
26
 Java and colleagues (2007) characterised most
tweets as “daily chatter”.
 Pear Analytics stud...
Twitter Evolution
27
Conversations evolved on Twitter
 @ symbol for replies (Honeycutt & Herring, 2009)
 RTs
 New studi...
Twitter Evolution
28
Kwak, H., Lee, C., Park, H., & Moon, S. (2010). What is Twitter, a Social Network or a News Media? In...
Selected Research Areas
29
de-banalising Twitter!
Selected Research Areas
30
Brand Communication
& Marketing
Crises & Natural
Disasters Elections & Politics
Popular Culture...
Technical Research
31
Named Entity Extraction Information Retrieval &
Ranking Sentiment Analysis
Network Analyses Trend De...
How to Study Twitter?
32
Twitter Data?
33
How to Collect Twitter Data?
34
Challenges:
Real-time archiving
obligatory
Limited to portions of
traffic
How to Collect Twitter Data?
35
Twitter APIs
 API = Application Programming Interface
 Interface to collect data from we...
How to Collect Twitter Data?
36
STREAMING API
- push-based, live stream of data
- Researchers need tools that maintain a c...
How to Collect Twitter Data?
37
 Sample (1% or 10% of all tweets, probably
random)
 Track (tweets including specific key...
How to Collect Twitter Data?
38
REST API
 Limited requests per hour
 Social graph data (who is following who)
 Access t...
How to Collect Twitter Data?
39
 Your Twapperkeeper
 Via RSS feed (e.g. google reader, thunderbird)
 Third parties ($)
...
Your Twapperkeeper
40
Your Twapperkeeper
41
Tweet Archivist
42
http://www.tweetarchivist.com/
GNIP
43
Examples
44
Twitter Visualisations
45
http://www.cci.edu.au/node/1362
The Australian Twitter-Sphere
Rhythm of a City
46
http://engineering.twitter.com/2012/06/studying-rapidly-evolving-user.html
Sentiments
47
http://www.ccs.neu.edu/home/amislove/twittermood/
Twitter in African Capitals
48
http://www.jeuneafrique.com/Article/ARTJAWEB20130215165826/internet-
libreville-accra-addis...
49
1. FC Köln (@fckoeln)
Borussia Mönchengladbach (@VfLBorussia)
BVB Dortmund 09 II (@BVB)
FC Bayern München (@BayMuenchen...
London Riots
50
http://www.guardian.co.uk/uk/2011/dec/07/twitter-riots-how-news-spread
51
Bruns, A., & Burgess, J. (2012). Notes towards the scientific study of Twitter. In Tokar, A., Beurskens, M., Keuneke, S...
ChallengesPart 3
It‘s not all about the numbers…
53
Big Data vs.
meaningful research
questions
Representativeness
54
Influenced by, e.g.:
 User statistics
 Time of data collection
Reliability
55
 Verified accounts
 Verified storys?
What should we measure?
56
What is a link, a follower, a
friend, a tweet worth?
 How to interpret users‘
activities?
What should we measure?
57
Typically:
- Tweets from a certain user / a group of users
- Tweets mentioning a certain users
...
Standard Metrics?
58
 Number of tweets (per period, per user)
 Number of users with at least one tweet
 Structural Anal...
Standards? Time Series
hours
Numberoftweetsperhour
By Cornelius Puschmann (@coffee001)
Standards? Networks (@, RT, follower)
By Cornelius Puschmann (@coffee001)
Standards? Active Users
Users and their tweets during #www2010
0
20
40
60
80
100
120
140
160
180
200
Numberoftweets
Standards? Active Users
0
5
10
15
20
25
30
35
40
Numberof@-messaes
@-Nachrichten gesendet @-Nachrichten empfangen@messages...
Legal vs. Ethical?
63
Legal Questions
64
 Grey area in law
Basics:
 Twitter Terms of Services
 Twitter Rules of the Road
 Twitter Privacy Po...
Ethical Questions
65
 Not all that‘s legal is ethical
 How to deal with user data?
 How to anonomyse the data?
Legal and Ethical Questions
66
Currently: common sense
 Share as little individual-related data as possible
 Don‘t make ...
Data Access & Long Term Accessibility
67
today vs. tomorrow
Reproducibility
68
 Collecting the same data twice?
 Working with existing datasets?
 Cleaning the data?
Preservation
69
 Library of Congress
 ARCOMEM project
Thank you for your attention!
70
Upcoming
71
Edited Collection: Twitter and Society
Editors: Katrin Weller, Axel Bruns, Jean Burgess, Merja Mahrt
&Corneliu...
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Twitter research overview

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Overview / introduction to current Twitter research. This presentation was initially prepared for my colleagues at GESIS.

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Twitter research overview

  1. 1. TWITTER RESEARCH: STATE OF THE ART AND OPEN CHALLENGES Katrin Weller @kwelle katrin.weller@gesis.org 1 Präsentation im DAS Kolloquium Köln, 21. März 2013
  2. 2. Introduction to TwitterPart 1
  3. 3. Twitter: A Short Introduction 3 Jack Dorsey (2000): “twttr sketch”. http://www.flickr.com/photos/jackdorsey/182613360/
  4. 4. Twitter: A Short Introduction 4
  5. 5. Twitter: A Short Introduction 5 Tweet = 140 characters
  6. 6. Twitter: A Short Introduction 6 Followers and Followees
  7. 7. Twitter: A Short Introduction 7
  8. 8. Twitter: A Short Introduction 8
  9. 9. Twitter Terminology 9 Retweet (RT, via) Kooti, F., Yang, H., Cha, M., Gummadi, K.P. & Mason, W.A. (2012). The Emergence of Conventions in Online Social Networks. Proceedings of the International Conference on Weblogs and Social Media (ICWSM 2012), Dublin.
  10. 10. Twitter Terminology 10 @message (≠ direct message)
  11. 11. Twitter Terminology 11 # Hashtags
  12. 12. Hashtags 12  Memes  Conventions  Trends  Influence  #becareful!!! March 19, 2012
  13. 13. Twitter: Numbers 13  Founded in 2006 (independent Plattform since 2007)  March 2012: 140 million active users and 340 million Tweets a day  December 2012: more than 200 million users  USA, 2012: 15% of online adults use Twitter  Germany, 2012: 4% of population PEW Internet: http://www.pewinter net.org/Reports/201 2/Twitter-Use- 2012.aspx Twitter Blog: http://blog.twitt er.com/2012/0 3/twitter-turns- six.html @twitter: https://twitter.co m/twitter/status /28105165223 5087872 ARD/ZDF online Studie http://www.ard-zdf- onlinestudie.de/fileadmin/ Online12/0708- 2012_Busemann_Gscheidl e.pdf
  14. 14. Twitter vs. Facebook 14 In Germany Facebook: 72.1% (of Internet users) Twitter: 10.5% (of Internet users) German Social Media Consumer Report: http://www.socialmediathinklab .com/wp- content/uploads/2013/02/W WU_Social-Media-Consumer- Report_0213_Ansicht.pdf
  15. 15. Twitter: Trivia 15  Twitter users with most followers?  Trends 2012: olympics, US election  Most retweeted: https://2012.twitter.com/de/golden-tweets.html
  16. 16. Twitter: Popular Users 16 March,2013,http://twittercounter.com/pages/100
  17. 17. Twitter Tools 17
  18. 18. Twitter Tools 18
  19. 19. 19
  20. 20. Twitter ResearchPart 2
  21. 21. Development of Twitter Research 21 0 200 400 600 800 1000 1200 2007 2008 2009 2010 2011 2012 Scopus WoS SSCI Scopus: Social Science only
  22. 22. Twitter vs. Facebook 22 0 200 400 600 800 1000 1200 1400 2007 2008 2009 2010 2011 2012 Scopus: Twitter Scopus: Facebook
  23. 23. Scopus: Publications from 70 countries 23 United States; 958 United Kingdom; 174 Japan; 166China; 140Germany; 115 Australia; 95 Canada; 77 Spain; 77 South Korea; 73 India; 58
  24. 24. Scopus: Publications by Discipline 24 1621 519 375 291 284 178 115 98 48 41 0 200 400 600 800 1000 1200 1400 1600 1800 Computer Science Social Sciences Engineering Mathematics Business, Management and Accounting Medicine Decision Sciences Arts and Humanities Materials Science Psychology Top ten subject areas for Twitter research based on Scopus (TITLE-ABS-KEY(Twitter) AND PUBYEAR > 2006)
  25. 25. Why Study Twitter? 25 pointless babble?
  26. 26. Early Twitter Research 26  Java and colleagues (2007) characterised most tweets as “daily chatter”.  Pear Analytics study: 40% of tweets are pointless babble (Kelly, 2009). Java, A., Song, X., Finin, T., & Tseng, B. (2007). Why we twitter: understanding microblogging usage and communities. In Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis (WebKDD/SNA-KDD ’07). ACM, New York, NY, USA, 56-65. DOI=10.1145/1348549.1348556 http://doi.acm.org/10.1145/1348549.1348556 Kelly, R. (2009). Twitter Study. Pear Analytics, retrieved from http://www.pearanalytics.com/wp-content/uploads/2012/12/Twitter-Study- August-2009.pdf
  27. 27. Twitter Evolution 27 Conversations evolved on Twitter  @ symbol for replies (Honeycutt & Herring, 2009)  RTs  New studies focusing on communication structures and networks Honeycutt, C., and Herring, Susan C. (2009). Beyond microblogging: Conversation and collaboration via Twitter. Proceedings of the Forty-Second Hawaii International Conference on System Sciences.Los Alamitos, CA IEEE Press.
  28. 28. Twitter Evolution 28 Kwak, H., Lee, C., Park, H., & Moon, S. (2010). What is Twitter, a Social Network or a News Media? In Proceedings of the 19th International World Wide Web (WWW) Conference, April 26-30, 2010, Raleigh NC, USA. Follow me?
  29. 29. Selected Research Areas 29 de-banalising Twitter!
  30. 30. Selected Research Areas 30 Brand Communication & Marketing Crises & Natural Disasters Elections & Politics Popular Culture Education & Scholarly Communication Health Care & Diseases
  31. 31. Technical Research 31 Named Entity Extraction Information Retrieval & Ranking Sentiment Analysis Network Analyses Trend Detection
  32. 32. How to Study Twitter? 32
  33. 33. Twitter Data? 33
  34. 34. How to Collect Twitter Data? 34 Challenges: Real-time archiving obligatory Limited to portions of traffic
  35. 35. How to Collect Twitter Data? 35 Twitter APIs  API = Application Programming Interface  Interface to collect data from web applications  Streaming API, Rest APIs, Search API
  36. 36. How to Collect Twitter Data? 36 STREAMING API - push-based, live stream of data - Researchers need tools that maintain a connection to this stream.
  37. 37. How to Collect Twitter Data? 37  Sample (1% or 10% of all tweets, probably random)  Track (tweets including specific keywords)  Follow (tweets from selected users)  Locations (for geotagged tweets)
  38. 38. How to Collect Twitter Data? 38 REST API  Limited requests per hour  Social graph data (who is following who)  Access trending topics  And many more
  39. 39. How to Collect Twitter Data? 39  Your Twapperkeeper  Via RSS feed (e.g. google reader, thunderbird)  Third parties ($)  Your own programmes  Gnip / DataSift
  40. 40. Your Twapperkeeper 40
  41. 41. Your Twapperkeeper 41
  42. 42. Tweet Archivist 42 http://www.tweetarchivist.com/
  43. 43. GNIP 43
  44. 44. Examples 44
  45. 45. Twitter Visualisations 45 http://www.cci.edu.au/node/1362 The Australian Twitter-Sphere
  46. 46. Rhythm of a City 46 http://engineering.twitter.com/2012/06/studying-rapidly-evolving-user.html
  47. 47. Sentiments 47 http://www.ccs.neu.edu/home/amislove/twittermood/
  48. 48. Twitter in African Capitals 48 http://www.jeuneafrique.com/Article/ARTJAWEB20130215165826/internet- libreville-accra-addis-abebareseaux-sociaux-les-capitales-africaines-de- twitter-quartier-par-quartier.html#Tunis
  49. 49. 49 1. FC Köln (@fckoeln) Borussia Mönchengladbach (@VfLBorussia) BVB Dortmund 09 II (@BVB) FC Bayern München (@BayMuenchen) FC Schalke 04 II (@s04, official) FC Schalke 04 I (@FCSchalke04, inofficial) Hamburger SV (@HSV) SV Werder Bremen I (@Werder_Bremen) SV Werder Bremen II (@werderbremen) 0 10000 20000 30000 40000 50000 60000 70000 80000 Jun 11 Jul 11 Aug 11 Sep 11 Oct 11 Nov 11 Dec 11 Jan 12 Feb 12 Mar 12 Apr 12 May 12 Jun 12 numberoffollowers month 1. FC Augsburg (@FCAugsburg) 1. FC Kaiserslautern (@Rote_Teufel)* 1. FC Köln (@fckoeln) 1. FC Nürnberg (@1_fc_nuernberg) 1. FSV Mainz 05 (1FSVMainz05) 1899 Hoffenheim (achtzehn99) Bayer 04 Leverkusen (@bayer04fussball) Borussia Mönchengladbach (@VfLBorussia) BVB Dortmund 09 I (@BVBDortmund09) BVB Dortmund 09 II (@BVB) FC Bayern München (@BayMuenchen) FC Schalke 04 II (@s04, official) FC Schalke 04 I (@FCSchalke04, inofficial) Hamburger SV (@HSV) Hannover 96 I (@ichbin96) Hannover 96 II (@hannover96) Hertha BSC Berlin (@HerthaBSC)* SC Freiburg (@sc_freiburg) SV Werder Bremen I (@Werder_Bremen) SV Werder Bremen II (@werderbremen) VfB Stuttgart (@VfB) VfL Wolfsburg (@VfL_Wolfsburg) Twitterleague: German Bundesliga Clubs during Season 2011/12 See also: Weller, K., & Bruns, A. (2013). Das Spiel dauert 140 Zeichen. Wie deutsche Fußballvereine Twitter für Marketing und Fan-Kommunikation entdecken. In: HiER 2013. Proceedings des 8. Hildesheimer Evaluierungs- und Retrievalworkshop, April 2013: https://www.uni- hildesheim.de/media/fb3/informationswissenschaft/HIER/hier2013_proceedings_vorab.pdf
  50. 50. London Riots 50 http://www.guardian.co.uk/uk/2011/dec/07/twitter-riots-how-news-spread
  51. 51. 51 Bruns, A., & Burgess, J. (2012). Notes towards the scientific study of Twitter. In Tokar, A., Beurskens, M., Keuneke, S., Mahrt, M., Peters, I., Puschmann, C., van Treeck, T., & Weller, K. (Eds.). (2012). Science and the Internet (pp. 159-169). Düsseldorf: Düsseldorf University Press http://nfgwin.uni-duesseldorf.de/sites/default/files/Bruns.pdf
  52. 52. ChallengesPart 3
  53. 53. It‘s not all about the numbers… 53 Big Data vs. meaningful research questions
  54. 54. Representativeness 54 Influenced by, e.g.:  User statistics  Time of data collection
  55. 55. Reliability 55  Verified accounts  Verified storys?
  56. 56. What should we measure? 56 What is a link, a follower, a friend, a tweet worth?  How to interpret users‘ activities?
  57. 57. What should we measure? 57 Typically: - Tweets from a certain user / a group of users - Tweets mentioning a certain users - Tweets that contain a specific word or hashtag - Random tweets Also: - Follower numbers - Tweets containg (specific) URLs
  58. 58. Standard Metrics? 58  Number of tweets (per period, per user)  Number of users with at least one tweet  Structural Analysis of Tweets:  Original tweets, RTs, (modified RTs), @message  Tweets containing URLs
  59. 59. Standards? Time Series hours Numberoftweetsperhour By Cornelius Puschmann (@coffee001)
  60. 60. Standards? Networks (@, RT, follower) By Cornelius Puschmann (@coffee001)
  61. 61. Standards? Active Users Users and their tweets during #www2010 0 20 40 60 80 100 120 140 160 180 200 Numberoftweets
  62. 62. Standards? Active Users 0 5 10 15 20 25 30 35 40 Numberof@-messaes @-Nachrichten gesendet @-Nachrichten empfangen@messages sent @messages received
  63. 63. Legal vs. Ethical? 63
  64. 64. Legal Questions 64  Grey area in law Basics:  Twitter Terms of Services  Twitter Rules of the Road  Twitter Privacy Policy
  65. 65. Ethical Questions 65  Not all that‘s legal is ethical  How to deal with user data?  How to anonomyse the data?
  66. 66. Legal and Ethical Questions 66 Currently: common sense  Share as little individual-related data as possible  Don‘t make tweet collections publicly available
  67. 67. Data Access & Long Term Accessibility 67 today vs. tomorrow
  68. 68. Reproducibility 68  Collecting the same data twice?  Working with existing datasets?  Cleaning the data?
  69. 69. Preservation 69  Library of Congress  ARCOMEM project
  70. 70. Thank you for your attention! 70
  71. 71. Upcoming 71 Edited Collection: Twitter and Society Editors: Katrin Weller, Axel Bruns, Jean Burgess, Merja Mahrt &Cornelius Puschmann. To be published 2013, with Peter Lang.

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