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Rijke. Adding semantics to microblog posts (2012)
| Venue: | In WSDM ’12. ACM |
| Citations: | 64 - 14 self |
BibTeX
@INPROCEEDINGS{Meij12rijke.adding,
author = {Edgar Meij and Wouter Weerkamp and Maarten De Rijke},
title = {Rijke. Adding semantics to microblog posts},
booktitle = {In WSDM ’12. ACM},
year = {2012}
}
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Abstract
Microblogs have become an important source of information for the purpose of marketing, intelligence, and reputation management. Streams of microblogs are of great value because of their direct and real-time nature. Determining what an individual microblog post is about, however, can be non-trivial because of creative language usage, the highly contextualized and informal nature of microblog posts, and the limited length of this form of communication. We propose a solution to the problem of determining what a mi-croblog post is about through semantic linking: we add seman-tics to posts by automatically identifying concepts that are seman-tically related to it and generating links to the corresponding Wiki-pedia articles. The identified concepts can subsequently be used for, e.g., social media mining, thereby reducing the need for man-ual inspection and selection. Using a purpose-built test collection of tweets, we show that recently proposed approaches for semantic linking do not perform well, mainly due to the idiosyncratic nature of microblog posts. We propose a novel method based on machine learning with a set of innovative features and show that it is able to achieve significant improvements over all other methods, espe-cially in terms of precision.
Keyphrases
microblog post mi-croblog post purpose-built test collection significant improvement man-ual inspection semantic linking identified concept great value idiosyncratic nature important source informal nature creative language usage corresponding wiki-pedia article real-time nature social medium mining innovative feature limited length individual microblog post reputation management machine learning novel method
