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2014 | OriginalPaper | Chapter

Vector Space Models for the Classification of Short Messages on Social Network Services

Authors : Ricardo Lage, Peter Dolog, Martin Leginus

Published in: Web Information Systems and Technologies

Publisher: Springer Berlin Heidelberg

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Abstract

In this chapter we review vector space models to propose a new one based on the Jensen-Shannon divergence with the goal of classifying ignored short messages on a social network service. We assume that ignored messages are those published ones that were not interacted with. Our goal then is to attempt to classify messages to be published as ignored to discard them from a set messages that can be used by a recommender system. To evaluate our model, we conduct experiments comparing different models on a Twitter dataset with more than 13,000 Twitter accounts. Results show that our best model tested obtained an average accuracy of 0.77, compared to 0.74 from a model from the literature. Similarly, this method obtained an average precision of 0.74 compared to 0.58 from the second best performing model.

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previous chapter Status Quo and Best Practices of App Development in Regional Companies

next chapter FactRunner: A New System for NLP-Based Information Extraction from Wikipedia

http://www.tweetstats.com/graphs/nytimes/zoom/2012/Sep

These numbers are based on discussions in blog posts such as in http://thenextweb.com/twitter/2012/01/07/interesting-fact-most-tweets-posted-are -approximately-30-characters-long/ and http://www.ayman-naaman.net/2010/04/21/how-many-characters-do-you-tweet/. But they do not provide an average. In our own dataset presented in Sect. 4.1, the average number of characters in a tweet is 84.

Note that we do not normalize our tf-idf model based on message length since all tend to have similar sizes [18].

https://dev.twitter.com/docs/api/1/get/statuses/sample

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Title: Vector Space Models for the Classification of Short Messages on Social Network Services
Authors: Ricardo Lage
Peter Dolog
Martin Leginus
Publisher: Springer Berlin Heidelberg
Book: Web Information Systems and Technologies
Print ISBN: 978-3-662-44299-9

Electronic ISBN: 978-3-662-44300-2

Copyright Year: 2014
DOI: https://doi.org/10.1007/978-3-662-44300-2_13

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