Twitter Trend Extraction: A Graph-based Approach for Tweet and Hashtag Ranking, Utilizing No-Hashtag Tweets

Zahra Majdabadi, Behnam Sabeti, Preni Golazizian, Seyed Arad Ashrafi Asli, Omid Momenzadeh, Reza Fahmi

Abstract
Twitter has become a major platform for users to express their opinions on any topic and engage in debates. User debates and interactions usually lead to massive content regarding a specific topic which is called a Trend. Twitter trend extraction aims at finding these relevant groups of content that are generated in a short period. The most straightforward approach for this problem is using Hashtags, however, tweets without hashtags are not considered this way. In order to overcome this issue and extract trends using all tweets, we propose a graph-based approach where graph nodes represent tweets as well as words and hashtags. More specifically, we propose a modified version of RankClus algorithm to extract trends from the constructed tweets graph. The proposed approach is also capable of ranking tweets, words and hashtags in each trend with respect to their importance and relevance to the topic. The proposed algorithm is used to extract trends from several twitter datasets, where it produced consistent and coherent results.
Anthology ID:
2020.lrec-1.762
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
6213–6219
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.762
DOI:
Bibkey:
Cite (ACL):
Zahra Majdabadi, Behnam Sabeti, Preni Golazizian, Seyed Arad Ashrafi Asli, Omid Momenzadeh, and Reza Fahmi. 2020. Twitter Trend Extraction: A Graph-based Approach for Tweet and Hashtag Ranking, Utilizing No-Hashtag Tweets. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 6213–6219, Marseille, France. European Language Resources Association.
Cite (Informal):
Twitter Trend Extraction: A Graph-based Approach for Tweet and Hashtag Ranking, Utilizing No-Hashtag Tweets (Majdabadi et al., LREC 2020)
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