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Erschienen in:
A Randomized Approach for Structural and Message Based Private Friend Recommendation in Online Social Networks Kapitel lesen Erstes Kapitel lesen

2014 | OriginalPaper | Buchkapitel

Context Based Semantic Relations in Tweets

verfasst von : Ozer Ozdikis, Pinar Senkul, Halit Oguztuzun

Erschienen in: State of the Art Applications of Social Network Analysis

Verlag: Springer International Publishing

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Abstract

Twitter, a popular social networking platform, provides a medium for people to share information and opinions with their followers. In such a medium, a flash event finds an immediate response. However, one concept may be expressed in many different ways. Because of users’ different writing conventions, acronym usages, language differences, and spelling mistakes, there may be variations in the content of postings even if they are about the same event. Analyzing semantic relationships and detecting these variations have several use cases, such as event detection, and making recommendations to users while they are posting tweets. In this work, we apply semantic relationship analysis methods based on term co-occurrences in tweets, and evaluate their effect on detection of daily events from Twitter. The results indicate higher accuracy in clustering, earlier event detection and more refined event clusters.

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Vorheriges Kapitel A Randomized Approach for Structural and Message Based Private Friend Recommendation in Online Social Networks
Nächstes Kapitel Fast Exact and Approximate Computation of Betweenness Centrality in Social Networks
Fußnoten
2
Twitter4J homepage, http://​twitter4j.​org.
 
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Metadaten
Titel
Context Based Semantic Relations in Tweets
verfasst von
Ozer Ozdikis
Pinar Senkul
Halit Oguztuzun
Copyright-Jahr
2014
Buch
State of the Art Applications of Social Network Analysis

Print ISBN: 978-3-319-05911-2

Electronic ISBN: 978-3-319-05912-9

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-319-05912-9_2

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