Identifying topic relevant hashtags in Twitter streams

• Type: Article in International Scientific Journal
• Date: 2019

Authors

Figueiredo, F (Author) Other; Jorge, AM (Author) FCUP

Journal

Title: Information Sciences

Vol. 505

Pages: 65-83

ISSN: 0020-0255

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 5 Citations

Other information

Authenticus ID: P-00Q-W8W

DOI: 10.1016/j.ins.2019.07.062

Abstract (EN): Hashtags have become a crucial social media tool. The categorization of posts in a simple and informal way helps to spread the content through the web. At the same time, it enables users to easily find messages within a specific topic. However, the flexibility provided to use and create a hashtag carries some problems. Equivalent expressions, like synonyms, are handled like entirely different words. On the other hand, the same hashtag may refer to different topics. In this paper, we present TORHID (Topic Relevant Hashtag Identification), a method that employs topic modeling with the purpose of retrieving and identifying hashtags relevant to a specific topic in Twitter streams, starting from a seed hashtag and resorting to a classifier to remove non relevant hashtags. The result is a network of hashtags related to the seed, that we can use to deepen the initial search.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 19