Combined analysis of news and Twitter messages

Show full item record



Permalink

http://hdl.handle.net/10138/42507

Citation

Du , M , Kangasharju , J , Karkulahti , O , Pivovarova , L & Yangarber , R 2013 , Combined analysis of news and Twitter messages . in Proceedings of the Joint Workshop on NLP &LOD and SWAIE : SemanticWeb, Linked Open Data and Information Extraction . Hissar , pp. 41-48 , RANLP 2013 Workshop on Semantic Web and Information Extraction , Hissar , Bulgaria , 13/09/2013 . < https://www.aclweb.org/anthology/W/W13/W13-52.pdf >

Title: Combined analysis of news and Twitter messages
Author: Du, Mian; Kangasharju, Jussi; Karkulahti, Ossi; Pivovarova, Lidia; Yangarber, Roman
Contributor: University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
Date: 2013
Language: eng
Number of pages: 8
Belongs to series: Proceedings of the Joint Workshop on NLP&LOD and SWAIE SemanticWeb, Linked Open Data and Information Extraction
ISBN: 978-954-452-025-0
URI: http://hdl.handle.net/10138/42507
Abstract: While it is widely recognized that streams of social media messages contain valuable information, such as important trends in the users’ interest in consumer products and markets, uncovering such trends is problematic, due to the extreme volumes of messages in such media. In the case Twitter messages, following the interest in relation to all known products all the time is technically infeasible. IE narrows topics to search. In this paper, we present experiments on using deeper NLP-based processing of product-related events mentioned in news streams to restrict the volume of tweets that need to be considered, to make the problem more tractable. Our goal is to analyze whether such a combined approach can help reveal correlations and how they may be captured.
Subject: 113 Computer and information sciences
Twitter
social media
Information Extraction
Rights:


Files in this item

Total number of downloads: Loading...

Files Size Format View
2013_ranlp_tp.pdf 571.8Kb PDF View/Open

This item appears in the following Collection(s)

Show full item record