Paper Info
Title
Uncovering News-Twitter Reciprocity via Interaction Patterns.
Abstract
In recent years, the amount of information shared (both implicit and explicit) between traditional news media and social media sources like Twitter has grown at a prolific rate. Traditional news media is dependent on social media to help identify emerging developments; social media is dependent on news media to supply information in certain categories. In this paper, we present a principled framework for understanding their symbiotic relationship, with the goal of (1) understanding the type of information flow between news articles and the Twitterverse by classifying it into four states; (2) chaining similar news articles together to form story chains and extracting interaction patterns for each story chain in terms of interaction states of news articles in the story chain, and (3) identifying major interaction patterns by clustering story chains and understanding their differences by identifying main topics of interest within such clusters.
Year
DOI
Venue
2015
10.1145/2808797.2809329
ASONAM
Keywords
Field
DocType
news-Twitter reciprocity uncovering,interaction patterns,traditional news media,social media sources,symbiotic relationship,news articles,Twitterverse,story chain clustering
Media relations,Information flow (information theory),Chaining,World Wide Web,Social media,Social media optimization,Computer science,News media,Reciprocity (social psychology),Market research
Conference
Citations 
PageRank 
References 
3
0.38
17
Authors
4
Name
Order
Citations
PageRank
Yue Ning1539.74
Sathappan Muthiah21117.80
Ravi Tandon349857.91
Naren Ramakrishnan41913176.25