posts tagged ‘twitter’

Languages and social network behaviors: Top 10 languages on Twitter

26 April 2011 | Lichan Hong

There's a tendency on the part of designers, researchers, and others to assume that English-language users' behaviors in social networks generalize to that of other language users. But in a recent study where we examined 62 million tweets collected over a four-week period, we found significant differences in how people of different language backgrounds used features such as URLs, hashtags, mentions, replies, and retweets. But first: how did we examine this large-scale data set?

Further details on ‘Location’ field behavior on Twitter

25 January 2011 | ed h. chi

There are of course a lot more details on the 'Location' field study in the previous post, which was covered by various press outlets (Seattle PI, AllThingD, ReadWriteWeb, NYTimes.) There are several further details that're worth pondering about: Fir...

Further details on ‘Location’ field behavior on Twitter

25 January 2011 | ed h. chi

There are of course a lot more details on the 'Location' field study in the previous post, which was covered by various press outlets (Seattle PI, AllThingD, ReadWriteWeb, NYTimes.) There are several further details that're worth pondering about: Fir...

Want to be retweeted? Add URLs to your tweets!

16 August 2010 | Lichan Hong

In a previous post, I described a recent study in which we found that including hashtags in a tweet enhances the retweetability of the tweet. In this post, I'll focus on another factor that might affect retweetability: the URL.

Want to be Retweeted? Add Hashtags to Your Tweets!

9 August 2010 | Editor

In a recent study, Bongwon Suh, Peter Pirolli, Ed H. Chi, and I examined what factors might affect retweetability of a tweet. We will report our findings in an upcoming paper this August in the Second IEEE International Conference on Social Computing [1]. In this post, I focus on a factor that we found to correlate with retweetability: hashtag.

Before I dive into the details, here is some information about the dataset that we used in our study: From Twitter's Spritzer feed, we collected a random sample of public tweets from January 18, 2010 to March 8, 2010, yielding about 74 million tweets. That is, we collected about 1.5 million tweets per day, representing approximately 2-3% of 50 million tweets appearing on Twitter daily.

For each of these 74 million tweets, we scanned for a variety of retweet markers such as "RT @", "RT:@", "retweeting @", "retweet @", "via @", "thx @", "HT @", and "r @" [2]. We found that there are about 8.24 million retweets, accounting for 11.1% of all the tweets. Next, we searched for those tweets and retweets that contain at least one hashtag. We found that 10.1% of tweets and 20.8% of retweets include hashtags, suggesting that a tweet with hashtags is more likely to get retweeted.

We further investigated whether the retweetability of a tweet has anything to do with the type of hashtag it contains. Analyzing the 74 million tweets, we identified the 20 most popular hashtags used in our tweets and the number of tweets containing each hashtag:

On the other hand, the following table shows the 20 most popular hashtags used in our 8.24 million retweets and the number of retweets containing each hashtag:

As can be seen, these two lists of hashtags do not match each other exactly. For example, #jobs appears only in the first list, while #idothat2 appears only in the second list. That is, the fact that a hashtag is frequently used in the tweets does not guarantee that it is also frequently used in the reweets, and vice versa.

For each hashtag, we computed a retweet rate by dividing the number of retweets containing the hashtag by the number of tweets containing the hashtag. We then normalized the rate so that a value of 1.0 represents the average retweet rate of 11.1%. For example, for #nowplaying, the retweet rate of 0.75 was calculated as (29,846/355,147)*(74/8.24). A hashtag with a retweet rate higher than 1.0 indicates that, compared to the average case, the tweets containing this hashtag have a higher chance of getting retweeted. The following table shows the retweet rates for the 10 most popular hashtags used in our tweets:

In the following plot, each point represents an individual hashtag. The X-axis is the popularity rank of hashtags based on how many tweets contain each hashtag. The Y-axis represents the retweet rates of hashtags as computed above.


From the figure, we see that the retweet rates vary greatly. Not all popular hashtags in tweets are popular in retweets. The type of hashtag does matter.

References
[1] Suh, B., Hong, L., Pirolli, P., and Chi, E. H. Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network. To appear in SocialCom'10.
[2] boyd, d., Golder, S., and Lotan, G. Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter. Proc. HICSS'10, 1-10.

Want to be Retweeted? Add Hashtags to Your Tweets!

9 August 2010 | Editor

In a recent study, Bongwon Suh, Peter Pirolli, Ed H. Chi, and I examined what factors might affect retweetability of a tweet. We will report our findings in an upcoming paper this August in the Second IEEE International Conference on Social Computing [1]. In this post, I focus on a factor that we found to correlate with retweetability: hashtag.

Before I dive into the details, here is some information about the dataset that we used in our study: From Twitter's Spritzer feed, we collected a random sample of public tweets from January 18, 2010 to March 8, 2010, yielding about 74 million tweets. That is, we collected about 1.5 million tweets per day, representing approximately 2-3% of 50 million tweets appearing on Twitter daily.

For each of these 74 million tweets, we scanned for a variety of retweet markers such as "RT @", "RT:@", "retweeting @", "retweet @", "via @", "thx @", "HT @", and "r @" [2]. We found that there are about 8.24 million retweets, accounting for 11.1% of all the tweets. Next, we searched for those tweets and retweets that contain at least one hashtag. We found that 10.1% of tweets and 20.8% of retweets include hashtags, suggesting that a tweet with hashtags is more likely to get retweeted.

We further investigated whether the retweetability of a tweet has anything to do with the type of hashtag it contains. Analyzing the 74 million tweets, we identified the 20 most popular hashtags used in our tweets and the number of tweets containing each hashtag:

On the other hand, the following table shows the 20 most popular hashtags used in our 8.24 million retweets and the number of retweets containing each hashtag:

As can be seen, these two lists of hashtags do not match each other exactly. For example, #jobs appears only in the first list, while #idothat2 appears only in the second list. That is, the fact that a hashtag is frequently used in the tweets does not guarantee that it is also frequently used in the reweets, and vice versa.

For each hashtag, we computed a retweet rate by dividing the number of retweets containing the hashtag by the number of tweets containing the hashtag. We then normalized the rate so that a value of 1.0 represents the average retweet rate of 11.1%. For example, for #nowplaying, the retweet rate of 0.75 was calculated as (29,846/355,147)*(74/8.24). A hashtag with a retweet rate higher than 1.0 indicates that, compared to the average case, the tweets containing this hashtag have a higher chance of getting retweeted. The following table shows the retweet rates for the 10 most popular hashtags used in our tweets:

In the following plot, each point represents an individual hashtag. The X-axis is the popularity rank of hashtags based on how many tweets contain each hashtag. The Y-axis represents the retweet rates of hashtags as computed above.


From the figure, we see that the retweet rates vary greatly. Not all popular hashtags in tweets are popular in retweets. The type of hashtag does matter.

References
[1] Suh, B., Hong, L., Pirolli, P., and Chi, E. H. Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network. To appear in SocialCom'10.
[2] boyd, d., Golder, S., and Lotan, G. Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter. Proc. HICSS'10, 1-10.

Short and Tweet: Experiments on Recommending Content from Information Streams (Specifically, Twitter)

21 April 2010 | ed h. chi

Information streams have recently emerged as a popular means for information awareness. By information streams we are referring to the general set of Web 2.0 feeds such as status updates on Twitter and Facebook, and news and entertainment in Google Rea...

Short and Tweet: Experiments on Recommending Content from Information Streams (Specifically, Twitter)

21 April 2010 | ed h. chi

Information streams have recently emerged as a popular means for information awareness. By information streams we are referring to the general set of Web 2.0 feeds such as status updates on Twitter and Facebook, and news and entertainment in Google Rea...