Enhancing Twitter Tweet Topic Understanding through Ensemble Learning

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Suraj Shinde Patil
Muskan Jain
Harsh Ahuja
Akshay Mathur

Abstract

Since Twitter’s introduction to social media of the hashtag as a content grouping label in 2007, the symbol and its associated usage as a classification la- bel have seen widespread adoption throughout social media and other platforms. While the content of a post can be conveniently classified using said post’s hash- tags, classifying posts that do not contain hashtags proves to be a much more challenging problem. In this paper, we propose a system for identifying a post’s hashtags using only the non-hashtag terms of the post and, by extension, address the issue of classifying the contents of posts that do not contain hashtags.

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[1]
Suraj Shinde Patil, Muskan Jain, Harsh Ahuja, and Akshay Mathur , Trans., “Enhancing Twitter Tweet Topic Understanding through Ensemble Learning”, IJITEE, vol. 13, no. 1, pp. 6–12, Feb. 2024, doi: 10.35940/ijitee.A9761.1213123.
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How to Cite

[1]
Suraj Shinde Patil, Muskan Jain, Harsh Ahuja, and Akshay Mathur , Trans., “Enhancing Twitter Tweet Topic Understanding through Ensemble Learning”, IJITEE, vol. 13, no. 1, pp. 6–12, Feb. 2024, doi: 10.35940/ijitee.A9761.1213123.
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