w ho g ives a t weet ? evaluating microblog content value

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W HO G IVES A T WEET ? Evaluating Microblog Content Value. Carnegie Mellon & Uni. Southampton MIT CSAIL Georgia Institute of Technology. Paul André @ paulesque Michael Bernstein Kurt Luther. ?. What content is valued, and why?. ?. What content is valued, and why?. - PowerPoint PPT Presentation

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WHO GIVES A TWEET?Evaluating Microblog Content Value

Paul André@paulesque

Michael

BernsteinKurt Luther

Carnegie Mellon & Uni. Southampton

MIT CSAILGeorgia Institute of Technology

?

?

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

wgat_user:

username:

RECRUITMENT

RECRUITMENT

RECRUITMENT

1,443 usersrated 43,738 tweetsfrom 21,014 Twitter accounts

entire dataset

RESULTS

36% Worth Reading39% Neutral

25% Not Worth Reading

41% Worth Readingaverage

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 tweetsGround truth + CrowdFlowerCohen’s Kappa: 0.62

Category labelsmore Information Sharing (49% vs 22%)

less Me Now (10% vs 40%)

+ inclusion of organizations

compared to random sample in Naaman

(2010)

RESULTS: CategoriesPredictor

Question to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence Maintenance

RESULTS: CategoriesPredictor

Question to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence Maintenance

“gud morning twits”

20%liked

45%disliked

RESULTS: CategoriesPredictor

Question to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence Maintenance

Odds Ratio2.832.692.692.472.051.891.57N/A

“gud morning twits”

20%liked

45%disliked

*p<.01˘trend p=.05

Odds Ratio2.832.692.692.472.051.891.57N/A

RESULTS: CategoriesPredictor

Question to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence Maintenance

“What'd they say?? @adam807 Dreamed I went to an @waitwait taping and they had to stop because a guest made @petersagal cry.”24%

liked34%

disliked*p<.01

˘trend p=.05

Odds Ratio2.832.692.692.472.051.89˘1.57N/A

RESULTS: CategoriesPredictor

Question to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence Maintenance

“tired and upset”

27%liked

25%disliked

*p<.01˘trend p=.05

Odds Ratio2.83*2.69*2.69*2.47*2.05˘1.89˘1.57N/A

RESULTS: CategoriesPredictor

Question to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence Maintenance *p<.01

˘trend p=.05

Odds Ratio2.83*2.69*2.69*2.47*2.05˘1.89˘1.57N/A

RESULTS: CategoriesPredictor

Question to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence Maintenance *p<.01

˘trend p=.05

Odds Ratio2.83*2.69*2.69*2.47*2.05˘1.89˘1.57N/A

RESULTS: CategoriesPredictor

Question to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence Maintenance *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 ProsaicTweets

“…and so what?”

“Just links are the worst thing in the world.”

Lack of ContextProfessional 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 DescriptionConciseness “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 RTingUse twitter-specific mechanisms (hashtags, @mentions, and DMs) appropriatelyUnique hashtag for questions is valuedConciseness, even with 140 chars, valuedHappy sentiments valued; whining disliked

IMPLICATIONS FOR PRACTICE

Exploring different communities on Twitter

Which results generalize

Rate author, not tweetUsers no longer followed

Self-ratingsTwitter as maintaining

awareness and relationships

LIMITATIONS

FUTURE WORK

DISCUSSION

Utilizing results:

Twitter’s simplicity vs. Facebook’s newsfeed complexity

Presentation:

Technological intervention:design tools to learn, filter, re-presentSocial 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 reactionsSample of 1,400 users and 43,000 ratings:

CONCLUSIONS

41% of feed worth readingInformation Sharing liked / Me Now dislikedReasons: 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 reactionsSample of 1,400 users and 43,000 ratings:

41% of feed worth readingInformation Sharing liked / Me Now dislikedReasons: context, commentary, conciseness, …Technological and social interventionsCONCLUSIONSCONCLUSIONSCONCLUSIONSThanks 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 HCIIMichael Bernstein – MIT CSAILKurt Luther – Georgia Tech GVU

RESULTSCategoriesPredictor Odds

Ratioz 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 1.26Presence Maintenance N/A N/A

RESULTSCategoriesQuestion to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence 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

RESULTSCategoriesQuestion to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence Maintenance

“The headline arouses my curiosity.”

“Wow. Didn’t know that was happening. Thanks for informing me.”

Information Sharing

RESULTSCategoriesQuestion to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence 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

RESULTSCategoriesQuestion to FollowersInformation SharingSelf-PromotionRandom ThoughtOpinion / ComplaintMe NowConversationPresence 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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