Extracting Temporally-Anchored Knowledge from Tweets
Description:
Twitter has quickly become one of the most popular social media sites. It has 313 million monthly active users, and 500 million tweets are published daily. With the massive number of tweets, Twitter users share information about a location along with the temporal awareness. In this work, I focus on tweets where author of the tweets exclusively mentions a location in the tweet. Natural language processing systems can leverage wide range of information from the tweets to build applications like …
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Date:
May 2018
Creator:
Doudagiri, Vivek Reddy
Partner:
UNT Libraries