W HO G IVES A T WEET ? Evaluating Microblog Content Value Paul André @paulesque Michael Bernstein...
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Transcript of W HO G IVES A T WEET ? Evaluating Microblog Content Value Paul André @paulesque Michael Bernstein...
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 users
rated 43,738 tweets
from 21,014 Twitter
accounts
entire dataset
RESULTS
36% Worth Reading39% 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 +
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 Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
RESULTS: CategoriesPredictor
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
“gud morning twits”
20%liked
45%disliked
RESULTS: CategoriesPredictor
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
Odds Ratio
2.83
2.69
2.69
2.47
2.05
1.89
1.57
N/A
“gud morning twits”
20%liked
45%disliked
*p<.01˘trend p=.05
Odds Ratio
2.83
2.69
2.69
2.47
2.05
1.89
1.57
N/A
RESULTS: CategoriesPredictor
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence 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%liked
34%disliked
*p<.01˘trend p=.05
Odds Ratio
2.83
2.69
2.69
2.47
2.05
1.89˘
1.57
N/A
RESULTS: CategoriesPredictor
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
“tired and upset”
27%liked
25%disliked
*p<.01˘trend p=.05
Odds Ratio
2.83*
2.69*
2.69*
2.47*
2.05˘
1.89˘
1.57
N/A
RESULTS: CategoriesPredictor
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
*p<.01˘trend p=.05
Odds Ratio
2.83*
2.69*
2.69*
2.47*
2.05˘
1.89˘
1.57
N/A
RESULTS: CategoriesPredictor
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence Maintenance
*p<.01˘trend p=.05
Odds Ratio
2.83*
2.69*
2.69*
2.47*
2.05˘
1.89˘
1.57
N/A
RESULTS: CategoriesPredictor
Question to Followers
Information Sharing
Self-Promotion
Random Thought
Opinion / Complaint
Me Now
Conversation
Presence 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 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
LIMITATIONS
FUTURE WORK
DISCUSSION
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 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 1.26
Presence Maintenance N/A N/A
RESULTSCategoriesQuestion 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
RESULTSCategoriesQuestion 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
RESULTSCategoriesQuestion 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
RESULTSCategoriesQuestion 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