This document summarizes a research project analyzing 1% of all tweets from a single day. The project aims to understand what an average day on Twitter looks like using a random sample. Key findings include identifying the top 100 hashtags, most mentioned users, and determining the sources tweets most frequently link to. Over 2.8 million unique user accounts were identified in the sample of over 4.5 million tweets. Analysis of hashtags found categories including celebrity, follow/retweet practices, status updates, memes and topics.

1. One Percent of Twitter
A digital methods winter school 2013 project
Bernhard, Julian, Nikolas, Liliana,
Lonneke, Esther, Erik, Carolin

2. Research Focus
Twitter research often based on the demarcation of
bottom-up query views, demarcated by hashtags, key
words, users, events, URLs etc.
This project follows a top-down sample-view by
retaining 1 % of all tweets from approx. 1 day.
1) How does an average day on Twitter
look like?
2) What are the specific affordances of
working with a random sample of Tweets?
3) What insights does this allow for
working with collections?

3. The Dataset
• Random Twitter Sample 1%
24.1.2013 19:28:57
25.1.2013 20:26:16
Total 4,577,401 tweets
• 50.09 tweets/s

4. Methodology
3. HASHTAGS
1. USERS Categorise & profile
Categorise top users top hashtags
2. URLs 4. GEOLOCATION
Determine the sources Plot tweets/language
tweets link to use on map

5. 2,849,881 different 100 most mentioned users
user accounts

6. 1% of
Celebrity TV Tags related to celebrities (Bieber, Rilakkuma) and TV (National TV Awards). E.g. ArianaRilakkumaC-
ontest, BELIEVEtour, BELIEVEacoustic, AmericanIdol Followback/Retweet'Social practice' tags that deal with
retwitting and following. E.g. TeamFollowBack, FOLLOWBACK, oomf, 500ADay, rt Undecided Undecided: Tags
#Twitter
Top 100 in Arabic. Status Update/Comment Tags that refer to particular topic. E.g. android, love, news, RealMadrid
Meme Tags that characterize user (Zodiac) or its status (current activity). E.g. Libra, Aquarius, nowplaying, time-
#hashtag wasting, facebook Topic Tags that refer to Internet memes. E.g. SosArgentinoSi, ChristianMingleUsernames,
categoryzed getowenonsportcenter, SalamMaulidurRasulFor, WesleyTakesOver, ballboy
Celebrity Followback & Retweet Undecided Status Update / Comment Meme Topic
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Only 13.27% of all
University of Amsterdam
digital methods winter school
January 2013
tweets have a hashtag.

7. Only 13.27% of Hashtags
all tweets have a
hashtag

8. Hashtags

9. Hashtags

10. Hashtags

11. Hashtags

12. Hashtags

13. Hashtags- Profile
1.ArianaRilakkumaContest
14388 total tweets
361 Retweets
10797 Users

14. Hashtags- Profile
1.ArianaRilakkumaContest
• 9 RTs: “I nominate @hopefulariana @arilujah @juicyari
@arianacoco @DEFYGRANDE @glitteryariana @biebersfries
#arianarilakkumacontest”
• 8 RTs: “RT @WoahItsTheBiebs: Retweet if you want me to
nominate you for #ArianaRilakkumaContest c:”
• 6 RTs: “i nomimate @SwedishAriana for
#ArianaRilakkumaContest !!”

15. Hashtags- Profile
2.TeamFollowBack
9332 total tweets
6677 Retweets
8702 Users

16. Hashtags- Profile
2.TeamFollowBack
• 20 RTs: RT @HitFollowsJp: █↓█↓ＲＥＴＷＥï¼
¥ï¼´â†“█↓█ ★ONLY★IF★YOU★WANT★NEW★
FOLLOWERS★ #HitFollowsTeam #OpenFollowTeam
#TeamFollowBack #TFBJP #FollowBackVIP ...”
• 15 RTs: “RT @ifollowbackjp: ã€Retweet Only If You Want New
Followers】#TeamFollowBack ♥#TeamFollowWack â™
¥#500aDay ♥#TFBJP ♥#MaxVIP ♥#SOUGOFOLLOW
♥#R ...”

17. Hashtags- Profile
3.rt
11538 total tweets
9456 Retweets
11076 Users

18. Hashtags- Profile
3.rt
• 14 RTs: “RT @ifollowbackjp: ã€Follow & RT】#TFBJP #SO
#FF #RT #F #IFA #TFW #FollowNGain #FOLLOWNGAIN
#OPENFOLLOW #INSTANTFOLLOW #TEAMFOLLOWBACK ...”
• 13 RTs: “RT @enyerbel: Da #RT *SI* QUIERES MAS
SEGUIDORES?? #SiguemeyTeSigo sigue a los que den #RT *
HAZLO Y COMPRUEBALO * RT RT * TODOS #FOLL ...”

19. Hashtags- Profile
4.CallOutSomebodyBeautiful
6052 total tweets
5864 Retweets
5951 Users

20. Hashtags- Profile
4.CallOutSomebodyBeautiful
• 17 RTs: “RT @kaungko: #CallOutSomebodyBeautiful You. Yes
you. The one with a nice personality and a good heart!
#ilikeyou #tweetsfrommyheart”
• 15 RTs: “RT @damnitstrue: #CallOutSomebodyBeautiful
every girl reading this.... you're beautiful. Smile. Life's too short
to be unhappy.”
• 14 RTs “RT @ExtraGrumpyCat: #CallOutSomebodyBeautiful
No. You're all ugly fucks.”

21. Hashtags- Profile
5.TFBJP
5780 total tweets
3417 Retweets
5278 Users

22. Hashtags- Profile
5.TFBJP
• 20 RTs: “RT @HitFollowsJp: █↓█↓ＲＥＴＷＥï¼
¥ï¼´â†“█↓█ ★ONLY★IF★YOU★WANT★NEW★
FOLLOWERS★ #HitFollowsTeam #OpenFollowTeam
#TeamFollowBack #TFBJP #FollowBackVIP ...”
• 15 RTs: “RT @ifollowbackjp: ã€Retweet Only If You Want New
Followers】#TeamFollowBack ♥#TeamFollowWack â™
¥#500aDay ♥#TFBJP ♥#MaxVIP ♥#SOUGOFOLLOW
♥#R ...”

23. Hashtags- Profile
6.ThingsIDoWhenIGetBored
4006 total tweets
3478 Retweets
3980 Users

24. Hashtags- Profile
6.ThingsIDoWhenIGetBored
• 35 RTs: “RT @JaiBrooks1: #ThingsIDoWhenIGetBored we all
know what giovanna does when she gets bored”
• 14 RTs: “RT @ExtraGrumpyCat: #ThingsIDoWhenIGetBored I
lay on the kitchen floor and pretend I'm a crumb.”
• 13 RTs “RT @stillblazingtho: #ThingsIDoWhenIGetBored I get
really stoned and then nothing I do is boring.”

25. URLs
Only 12.2% tweets
have a URL

26. URLs
Predominance of
platforms, little
presence of news.

27. GEO Location
All tweets & their geolocations

28. GEO Location
Tweets, geolocation & language.

29. Implications for research
Sample vs. Collection
• Only 12.2 % Hashtags: limits of collections demarcated
by hashtags.
• Suggesting decline of hashtag use practices?
• Also, only 12.2% contain URLs: limits of organising/
polarising tweets based on URLs.
Impact of the Social
• URLs: platforms followed by diverse longtail, very few
news sources.
• Hashtags predominantly used to gain followers &
retweets.

30. Thank you.
Questions?