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A Topic Modeling Method for Analyzes of Short-Text Data in Social Media Networks

10 pagesPublished: March 18, 2022

Abstract

Currently, many short texts are published online, especially on social media platforms. High impact events, for example, are highly commented on by users. Understanding the subjects and patterns hidden in online discussions is a very important task for contexts such as elections, natural disasters or major sporting events. However, many works of this nature use techniques that, despite showing satisfactory results, are not the most suitable when it comes to the short texts on social media and may suffer a loss in their results. Therefore, this paper presents a text mining method for messages published on social media, with a data pre-processing step and topic modeling for short texts. For this paper, we created a data set from real world tweets related to COVID-19 that is openly available1 for research purposes.

Keyphrases: short text, social media, text mining, topic modeling

In: Bidyut Gupta, Ajay Bandi and Mohammad Hossain (editors). Proceedings of 37th International Conference on Computers and Their Applications, vol 82, pages 112--121

Links:
BibTeX entry
@inproceedings{CATA2022:Topic_Modeling_Method_for,
  author    = {Ian Macedo Maiwald Santos and Luciana de Oliveira Rech and Ricardo Moraes},
  title     = {A Topic Modeling Method for Analyzes of Short-Text Data in Social Media Networks},
  booktitle = {Proceedings of 37th International Conference on Computers and Their Applications},
  editor    = {Bidyut Gupta and Ajay Bandi and Mohammad Hossain},
  series    = {EPiC Series in Computing},
  volume    = {82},
  pages     = {112--121},
  year      = {2022},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/HD6L},
  doi       = {10.29007/kr1z}}
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