Algorithm for Collecting and Sorting Data from Twitter through the Use of Dictionaries in Python

Authors

  • M. Beatriz Bernábe Loranca Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias de la Computación
  • Enrique Espinoza González Velázquez Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias de la Computación
  • Carmen Cerón Garnica Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias de la Computación

DOI:

https://doi.org/10.13053/cys-24-2-3408

Keywords:

Dictionary, twitter, NLP, python

Abstract

In this work we developed a tool for the classification of natural language in the social network Twitter: The main purpose is to divide in to twoclasses, the opinions that the users express about the political moment of the Mexican presidential elections in 2018. In this scenario, considering the information from the Tweets as corpus, these have been randomly downloaded from different users and with the tagging algorithm, it has been possible to identify the commentsin to two categories defined as praises and insults, which are directed towards the presidential candidates. The tool known as CLiPS from Python, has been used for such purpose with the inclusion of the tagging algorithm. Finally, the frequency of the terms is analyzed with descriptive statistics.

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Published

2020-06-23

Issue

Vol. 24 No. 2 (2020): Thematic Issue on Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez)

Section

Articles of the Thematic Issue

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