Understanding Twitter Hashtags from Latent Themes Using Biterm Topic Model

Author(s): Muzafar R. Bhat*, Burhan Bashir, Majid A. Kundroo, Naffi A. Ahanger

Journal Name: Recent Patents on Engineering

Volume 14 , Issue 3 , 2020

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Graphical Abstract:


Social media, in general, and Twitter, in particular, provide a space for discourses, contemporary narratives besides a discussion about few specific social issues. People respond to these events by writing short text messages.

Background: Hashtag “#”, a specific way to respond to a given raised discourse, narrative or any contemporary issue is usual to social media. Netizens write a short message as their opinion about any given issue represented using a given Hashtag. These small messages generally tend to have a latent topic (theme) as one’s opinion about it.

Objective: This research is aimed to extract, represent and understand those hidden themes.

Method: Biterm Topic Model (BTM) has been used in this study given its ability to deal with the short messages unlike Latent Dirichlet Allocation that expects a document to have a significant length.

Results: Twitter Hashtag #M comments. Data has been modelled with ten (10) topic.

Conclusion: The experimental results show that the proposed approach to understand the twittter hashtages from latent themes using biterm topic modelling method is very effective as compared to other methods.

Keywords: Topic Modelling, LDA, BTM, Social Media Analysis (SMA), twitter analysis, #MeToo.

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Article Details

Year: 2020
Published on: 19 January, 2021
Page: [440 - 447]
Pages: 8
DOI: 10.2174/1872212113666190328183517
Price: $25

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