Home » Research » Projects » Twitter vs. Wikipedia

Twitter vs. Wikipedia

Twitter vs. Wikipedia

BACKGROUND
Most of the tweets that users exchange on Twitter make implicit mentions of named-entities, which in turn can be mapped to corresponding Wikipedia articles using proper Entity Linking (EL) techniques. Some of those become trending entities on Twitter due to a long-lasting or a sudden effect on the volume of tweets where they are mentioned.

IDEA
We argue that the set of trending entities discovered from Twitter may help predict the volume of requests for relating Wikipedia articles. To validate this claim, we apply an EL technique to extract trending entities from a large dataset of public tweets. Then, we analyze the time series derived from the hourly trending score (i.e., an index of popularity) of each entity as measured by Twitter and Wikipedia, respectively.

RESULTS
Results revealed that Twitter actually leads Wikipedia by a lag of one hour, for more than 40% of the times.

REFERENCES

  • Ceccarelli, D., Lucchese, C., Orlando, S., and Tolomei, G.  Twitter Anticipates Bursts of Requests for Wikipedia ArticlesIn DUBMOD 2013 (upcoming).
    [PDF]

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: