Difference between revisions of "Compare Ramage Naaman"
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== Big Idea == | == Big Idea == | ||
| − | + | Both papers try to categorize tweets into certain categories that represent social meanings; they also try to see what can be found from the users whose posting practices are characterized by the type of tweets they publish. | |
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== Questions == | == Questions == | ||
1. How much time did you spend reading the (new, non-wikified) paper you summarized? | 1. How much time did you spend reading the (new, non-wikified) paper you summarized? | ||
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4. How much time did you spend reading background materiel? | 4. How much time did you spend reading background materiel? | ||
| − | + | 30 min | |
Latest revision as of 22:13, 5 November 2012
Two Papers
Problem
In the Ramage paper, the authors claims that the topics of all the tweets in Twitter can be classified into four categories:
- Substance Topics about events and ideas - Social Topics recognizing language used toward a social end - Status Topics denoting personal update - Style Topic that contains broader trends in language usage
They used the LDA topic model to model the latent topic information in each tweet.
In the Naaman paper, the authors also categorized the tweets from their underlying social meanings. However, they came up with 9 categories instead of 4:
- Information Sharing (IS) - Self Promotion (SP) - Opinions/Complaints (OC) - Statements and Random Thoughts (RT) - Me now (ME): talking about the user's own feelings - Question to followers (QF) - Presence Maintenance (PM) - Anecdote (me) (AM) - Anecdote (other) (AO)
Although the two categorizing methods are quite different, they both look into the latent meanings of the tweets and try to find the connection between the tweet's words and its social meaning.
Algorithm
The Ramage paper used LDA topic model to model each tweet, while the Naaman paper used various quantitative (statistical) methods, such as Pearson Chi-square, Kalensky’s analysis, Ward’s linkage cluster analysis.
Dataset
The Ramage paper used the Twitter data they crawled within one week. The Naaman paper used the Twitter data they crawled in the similar manner within three weeks.
Big Idea
Both papers try to categorize tweets into certain categories that represent social meanings; they also try to see what can be found from the users whose posting practices are characterized by the type of tweets they publish.
Questions
1. How much time did you spend reading the (new, non-wikified) paper you summarized?
1 hour
2. How much time did you spend reading the old wikified paper?
20 min
3. How much time did you spend reading the summary of the old paper?
10 min
4. How much time did you spend reading background materiel?
30 min
5. Was there a study plan for the old paper?
if so, did you read any of the items suggested by the study plan? and how much time did you spend with reading them?
No study plan
6. Give us any additional feedback you might have about this assignment.
