Methods and Challenges in Social Bots Detection: A Systematic Review

Morais, Daniel Marques Gomes; Digiampietri, Luciano Antônio

doi:10.1145/3466933.3466973

Cited by 3 publications

(1 citation statement)

References 39 publications

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“…In [de Morais and Digiampietri 2021] a systematic review is carried out on the detection of bots in social networking services, and brought as a conclusion the need for the emergence of new techniques for detecting bots, since the identified techniques could not guarantee the efficiency of the long-term approach.…”

Section: Related Workmentioning

confidence: 99%

Comparison of natural language processing techniques in social bot detection on Twitter during Brazilian presidential elections

Santos

Ferreira

et al. 2022

iSys

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Currently, there are thousands of social bots acting on different online social networks. Identifying them automatically is a computational challenge.This work uses different natural language processing methods to extract features from tweets collected during the 2018 Brazilian presidential election period in order to make the bot detection process more precise. The developed solution uses artificial intelligence techniques, combining feature selection and classification algorithms.The authors obtained the best results through a union of all the extracted features using the Random Forest classifier, achieving an precision of 0.86 for the bot class and AUC of 0.86.

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Section: Related Workmentioning

confidence: 99%

Comparison of natural language processing techniques in social bot detection on Twitter during Brazilian presidential elections

Santos

Ferreira

et al. 2022

iSys

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A Unified Neuro-Fuzzy Framework to Assess the User Credibility on Twitter

Laila

Jayashree

Vinuvarsidh

2023

IETE Journal of Research

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Ensino de Análise de Redes Sociais: Experiências na Escola de Artes, Ciências e Humanidades da Universidade de São Paulo

Digiampietri

2024

Anais Do XIII Brazilian Workshop on Social Network Analysis and Mining (BraSNAM 2024)

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Este artigo descreve a disciplina de Análise de Redes Sociais oferecida na Escola de Artes, Ciências e Humanidades da USP, que é ministrada desde 2022 para estudantes de graduação e pós-graduação em Sistemas de Informação, motivada pelo interesse crescente dos alunos e pela sua relevância multidisciplinar. Na graduação, observa-se elevado engajamento nos projetos práticos em grupo da disciplina. Já na pós-graduação, muitos estudantes cursam a disciplina como ingressante ou aluno especial, utilizando o aprendizado e a elaboração de projetos para aperfeiçoar sua formação como pesquisadores e/ou na preparação para o ingresso no programa de pós-graduação.

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Methods and Challenges in Social Bots Detection: A Systematic Review

Cited by 3 publications

References 39 publications

Comparison of natural language processing techniques in social bot detection on Twitter during Brazilian presidential elections

Comparison of natural language processing techniques in social bot detection on Twitter during Brazilian presidential elections

A Unified Neuro-Fuzzy Framework to Assess the User Credibility on Twitter

Ensino de Análise de Redes Sociais: Experiências na Escola de Artes, Ciências e Humanidades da Universidade de São Paulo

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