Evaluating Microblog Content: Who Gives a Tweet?

W
HO
 G
IVES
 A T
WEET
?
Evaluating Microblog Content Value
?
?
What content is valued, and why?
?
What content is valued, and why?
1.  
design implications
2.  
emerging norms and practice
DESIGN
Who Gives a Tweet?
anonymous feedback
from followers and
strangers
(analysis of follower ratings only)
DESIGN
anticipated reciprocity
Who Gives a Tweet?
anonymous feedback
from followers and
strangers
rate tweets
(provide us data)
receive value in return
(ratings from followers)
DESIGN
RECRUITMENT
RECRUITMENT
RECRUITMENT
1,443 users
rated 
43,738 tweets
from 21,014 Twitter accounts
entire dataset
RESULTS
36%
 
Worth
 Reading
39% Neutral
25%
 
Not Worth 
Reading
41% Worth Reading
average user
What content is valued,
and why?
What content is valued,
and why?
1.  
categories
2.  
reasons why
 
What content is valued,
and why?
 
4,220 tweets
Ground truth + CrowdFlower
Cohen’s Kappa: 0.62
 
Category labels
RESULTS:
Categories
RESULTS:
Categories
gud morning twits
20%
liked
45%
disliked
RESULTS:
Categories
gud morning twits
20%
liked
45%
disliked
*p<.01
˘trend p=.05
RESULTS:
Categories
“What'd they say??
@adam807 Dreamed I
went to an @waitwait
taping and they had to stop
because a guest made
@petersagal cry.”
24%
liked
34%
disliked
*p<.01
˘trend p=.05
RESULTS:
Categories
tired and upset
27%
liked
25%
disliked
*p<.01
˘trend p=.05
RESULTS:
Categories
*p<.01
˘trend p=.05
RESULTS:
Categories
*p<.01
˘trend p=.05
RESULTS:
Categories
*p<.01
˘trend p=.05
Not Worth 
Reading
RESULTS:
 
Reasons
Not Worth 
Reading
Old News
“Yes, I saw that first thing this morning.”
“Since your followers read the NYT
too, reposting NYT  URLs is tricky
unless you add something.”
No Personal Touch
Conversations
“Twitter’s fault; feels like listening
in on a private conversation”
RESULTS:
 
Reasons
Not Worth 
Reading
Banal or Prosaic
Tweets
“…and so what?”
“Just links are the worst thing in the world.”
Lack of Context
Professional vs
Personal Insight
“I unfollowed you for this tweet. I don’t
know you; I followed you b/c of you job.”
No Curiosity
“All the news I need is here. Not much of a
tease.”
RESULTS:
 
Reasons
Worth
 
Reading
RESULTS:
 
Reasons
Worth 
Reading
Valued 
Information
“interesting perspective on something I
know nothing about.”
“makes you want to know more.”
Appealing Description
Conciseness
“few words to say much, very clear.”
Human
“personal, honest, and transparent.”
RESULTS:
 
Reasons
Embed more 
context
 in tweets (be less cryptic)
Add extra 
commentary
, especially if RTing
Use 
twitter-specific mechanisms 
(hashtags,
@mentions,  and  DMs)  appropriately
Unique  
hashtag  for  questions  
is  valued
Conciseness
,  even  with  140  chars,  valued
Happy sentiments valued; 
whining disliked
IMPLICATIONS FOR PRACTICE
Exploring
 
different
communities
 
on Twitter
Which results generalize
Rate author
, not tweet
Users no longer followed
Self-ratings
Twitter as 
maintaining
awareness 
and relationships
LIMITATION
S
FUTURE WORK
DISCUSSIO
N
Utilizing results:
Twitter’s 
simplicity
 
vs. Facebook’s newsfeed 
complexity
Presentation:
Technological 
intervention:
design 
tools to learn, filter, re-present
Social 
intervention:
inform users of perceived value and reaction
Social media sites:
but also new questions of
content value and accepted practice
new 
connection opportunities
Design sites to 
elicit
 more 
subtle reactions
Sample of 1,400 users and 43,000 ratings:
CONCLUSIONS
41% of feed 
worth reading
Information Sharing 
liked / Me Now disliked
Reasons: 
context, commentary, conciseness, …
Technological and social 
interventions
Social media sites:
but also new questions of
content value and accepted practice
new 
connection opportunities
Design sites to 
elicit
 more 
subtle reactions
Sample of 1,400 users and 43,000 ratings:
41% of feed 
worth reading
Information Sharing 
liked / Me Now disliked
Reasons: 
context, commentary, conciseness, …
Technological and social 
interventions
CONCLUSIONS
CONCLUSIONS
CONCLUSIONS
Thanks for listening!
with thanks to Ed Cutrell, Robert Kraut, m.c.
schraefel, Ryen White, Sarita Yardi, HCII Social
Comp. group  and anonymous reviewers
Paul André – CMU HCII
Michael Bernstein – MIT CSAIL
Kurt Luther – Georgia Tech GVU
RESULTS
Categories
RESULTS
Categories
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
47% chance of being Worth Reading
“This is a good use of Twitter.”
“Gives one pause to think about the question posted.”
Questions to Followers
RESULTS
Categories
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
“The headline arouses my curiosity.”
“Wow. Didn’t know that was happening. 
Thanks for informing me.”
Information Sharing
RESULTS
Categories
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
22% chance of being Worth Reading
“Sorry, but I don’t care what people are eating.”
“Too much personal info.”
“He moans about this ALL THE TIME. Seriously.”
Me Now
RESULTS
Categories
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
Me Now
“Foursquare updates don’t need to be shared on
Twitter unless there’s a relevant update to be
made.”
“4sq, ffs.”
RECRUITMENT
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This study delves into the evaluation of microblog content value by analyzing feedback from followers and strangers on Twitter. The research explores the content that is valued and why, examining design implications, emerging norms, and practices in the online space. The study also discusses anticipated reciprocity in rating tweets and the overall user engagement with Twitter content.

  • Microblog Content
  • Twitter Analysis
  • User Feedback
  • Online Engagement
  • Social Media Research

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  1. WHO GIVES A TWEET? Evaluating Microblog Content Value Paul Andr @paulesque Carnegie Mellon & Uni. Southampton Michael Bernstein Kurt Luther MIT CSAIL Georgia Institute of Technology

  2. ?

  3. What content is valued, and why? ?

  4. What content is valued, and why? ? 1. design implications 2. emerging norms and practice

  5. Who Gives a Tweet? anonymous feedback from followers and strangers (analysis of follower ratings only) DESIGN DESIGN

  6. Who Gives a Tweet? anonymous feedback from followers and strangers rate tweets (provide us data) anticipated reciprocity receive value in return (ratings from followers) DESIGN DESIGN

  7. wgat_user: username: DESIGN DESIGN

  8. RECRUITMENT RECRUITMENT

  9. RECRUITMENT RECRUITMENT

  10. RECRUITMENT RECRUITMENT

  11. 1,443 users rated 43,738 tweets from 21,014 Twitter accounts

  12. 36% Worth Reading entire dataset 39% Neutral 25% Not Worth Reading 41% Worth Reading average user RESULTS RESULTS

  13. What content is valued, What content is valued, and why? and why?

  14. What content is valued, What content is valued, and why? and why? 1. categories 2. reasons why

  15. What content is valued, What content is valued, and why? and why? more Information Sharing (49% vs 22%) compared to random sample in Naaman (2010) Category labels 4,220 tweets less Me Now (10% vs 40%) Ground truth + CrowdFlower Cohen s Kappa: 0.62 + inclusion of organizations

  16. RESULTS: Categories Predictor Question to Followers Information Sharing Self-Promotion Random Thought Opinion / Complaint Me Now Conversation Presence Maintenance

  17. RESULTS: Categories Predictor Question to Followers Information Sharing Self-Promotion Random Thought Opinion / Complaint Me Now gud morning twits Conversation Presence Maintenance 20% liked 45% disliked

  18. RESULTS: Categories Predictor Odds Ratio Question to Followers 2.83 Information Sharing 2.69 Self-Promotion 2.69 Random Thought 2.47 Opinion / Complaint 2.05 Me Now 1.89 gud morning twits Conversation 1.57 Presence Maintenance N/A 20% liked 45% disliked *p<.01 trend p=.05

  19. RESULTS: Categories Predictor Odds Ratio Question to Followers 2.83 What'd they say?? @adam807 Dreamed I went to an @waitwait taping and they had to stop because a guest made @petersagal cry. Information Sharing 2.69 Self-Promotion 2.69 Random Thought 2.47 Opinion / Complaint 2.05 Me Now 1.89 Conversation 1.57 Presence Maintenance N/A 24% liked 34% disliked *p<.01 trend p=.05

  20. RESULTS: Categories Predictor Odds Ratio Question to Followers 2.83 Information Sharing 2.69 Self-Promotion 2.69 Random Thought 2.47 tired and upset Opinion / Complaint 2.05 Me Now 1.89 Conversation 1.57 Presence Maintenance N/A 27% liked 25% disliked *p<.01 trend p=.05

  21. RESULTS: Categories Predictor Odds Ratio Question to Followers 2.83* Information Sharing 2.69* Self-Promotion 2.69* Random Thought 2.47* Opinion / Complaint 2.05 Me Now 1.89 Conversation 1.57 Presence Maintenance N/A *p<.01 trend p=.05

  22. RESULTS: Categories Predictor Odds Ratio Question to Followers 2.83* Information Sharing 2.69* Self-Promotion 2.69* Random Thought 2.47* Opinion / Complaint 2.05 Me Now 1.89 Conversation 1.57 Presence Maintenance N/A *p<.01 trend p=.05

  23. RESULTS: Categories Predictor Odds Ratio Question to Followers 2.83* Information Sharing 2.69* Self-Promotion 2.69* Random Thought 2.47* Opinion / Complaint 2.05 Me Now 1.89 Conversation 1.57 Presence Maintenance N/A *p<.01 trend p=.05

  24. Not Worth Reading RESULTS: Reasons

  25. Not Worth Reading Old News Yes, I saw that first thing this morning. Since your followers read the NYT No Personal Touch too, reposting NYT URLs is tricky unless you add something. Conversations Twitter s fault; feels like listening in on a private conversation RESULTS: Reasons

  26. Not Worth Reading Banal or Prosaic Tweets and so what? Just links are the worst thing in the world. Lack of Context Professional vs Personal Insight I unfollowed you for this tweet. I don t know you; I followed you b/c of you job. No Curiosity All the news I need is here. Not much of a tease. RESULTS: Reasons

  27. Worth Reading RESULTS: Reasons

  28. Worth Reading Valued Information interesting perspective on something I know nothing about. Appealing Description makes you want to know more. Conciseness few words to say much, very clear. personal, honest, and transparent. Human RESULTS: Reasons

  29. IMPLICATIONS FOR PRACTICE IMPLICATIONS FOR PRACTICE Embed more context in tweets (be less cryptic) Add extra commentary, especially if RTing Use twitter-specific mechanisms (hashtags, @mentions, and DMs) appropriately Unique hashtag for questions is valued Conciseness, even with 140 chars, valued Happy sentiments valued; whining disliked

  30. LIMITATION S Exploring different communities on Twitter Which results generalize FUTURE WORK Rate author, not tweet Users no longer followed Self-ratings Twitter as maintaining awareness and relationships

  31. DISCUSSIO N Twitter s simplicity vs. Facebook s newsfeed complexity Presentation: Utilizing results: Technological intervention: design tools to learn, filter, re-present Social intervention: inform users of perceived value and reaction

  32. Social media sites: new connection opportunities but also new questions of content value and accepted practice Design sites to elicit more subtle reactions Sample of 1,400 users and 43,000 ratings: 41% of feed worth reading Information Sharing liked / Me Now disliked Reasons: context, commentary, conciseness, Technological and social interventions CONCLUSIONS

  33. Social media sites: new connection opportunities but also new questions of content value and accepted practice Design sites to elicit more subtle reactions Sample of 1,400 users and 43,000 ratings: 41% of feed worth reading Information Sharing liked / Me Now disliked Reasons: context, commentary, conciseness, Technological and social interventions Thanks for listening! with thanks to Ed Cutrell, Robert Kraut, m.c. schraefel, Ryen White, Sarita Yardi, HCII Social CONCLUSIONS CONCLUSIONS CONCLUSIONS Comp. group and anonymous reviewers Paul Andr CMU HCII Michael Bernstein MIT CSAIL Kurt Luther Georgia Tech GVU

  34. RESULTS Categories Predictor Odds Ratio z value Question to Followers 2.83 2.94* Information Sharing 2.69 3.05* Self-Promotion 2.69 2.61* Random Thought 2.47 2.89* Opinion / Complaint 2.05 1.93 Me Now 1.89 1.94 Conversation 1.57 1.26 Presence Maintenance N/A N/A

  35. RESULTS Categories Questions to Followers Questions to Followers Question to Followers Question to Followers Information Sharing Self-Promotion Random Thought Opinion / Complaint Me Now Conversation Presence Maintenance 47% chance of being Worth Reading This is a good use of Twitter. Gives one pause to think about the question posted.

  36. RESULTS Categories Question to Followers Information Sharing Information Sharing Self-Promotion Random Thought Opinion / Complaint Me Now Conversation Presence Maintenance Information Sharing Information Sharing The headline arouses my curiosity. Wow. Didn t know that was happening. Thanks for informing me.

  37. RESULTS Categories Question to Followers Information Sharing Self-Promotion Random Thought Opinion / Complaint Me Now Me Now Conversation Presence Maintenance Me Now Me Now 22% chance of being Worth Reading Sorry, but I don t care what people are eating. Too much personal info. He moans about this ALL THE TIME. Seriously.

  38. RESULTS Categories Question to Followers Information Sharing Self-Promotion Random Thought Opinion / Complaint Me Now Me Now Conversation Presence Maintenance Me Now Me Now Foursquare updates don t need to be shared on Twitter unless there s a relevant update to be made. 4sq, ffs.

  39. RECRUITMENT RECRUITMENT

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