Paper Info
Title
Linking Tweets To News: Is All News Of Interest?
Abstract
In a world where news is being generated almost continuously by many different news providers on many different platforms, it would be useful in certain industries to be able to determine how much of that news is actually being read, which news items are not interest generating or, indeed, if there are topics being discussed on Twitter that have not even been reported in the news. Twitter generates vast numbers of Tweets daily and has a massive active user base, so it is ideal as a way of gauging what news people are, or are not, interested in. This paper proposes a technique to efficiently relate Tweets to news articles and then to determine which news articles are of interest, which are not, and what is being discussed on Twitter that is not even in the news.
Year
DOI
Venue
2016
10.1007/978-3-319-44748-3_15
ARTIFICIAL INTELLIGENCE: METHODOLOGY, SYSTEMS, AND APPLICATIONS, AIMSA 2016
Keywords
Field
DocType
Twitter, News articles, Similarity, TF-IDF
World Wide Web,tf–idf,Computer science,News media,Artificial intelligence,Natural language processing
Conference
Volume
ISSN
Citations 
9883
0302-9743
1
PageRank 
References 
Authors
0.36
4
2
Name
Order
Citations
PageRank
Tariq Ahmad161.54
Allan Ramsay2238.97