Identifying communities in social media with deep learning

Pedro Barros, Isadora Cardoso-Pereira, Keila Barbosa, Alejandro C. Frery, Héctor Allende-Cid, Ivan Martins, Heitor S. Ramos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This work aims at analyzing twitter data to identify communities of Brazilian Senators. To do so, we collected data from 76 Brazilian Senators and used autoencoder and bi-gram to the content of tweets to find similar subjects and hence cluster the senators into groups. Thereafter, we applied an unsupervised sentiment analysis to identify the communities of senators that share similar sentiments about a selected number of relevant topics. We find that is able to create meaningful clusters of tweets of similar contents. We found 13 topics all of them relevant to the current Brazilian political scenario. The unsupervised sentiment analysis shows that, as a result of the complex political system (with multiple parties), many senators were identified as independent (19) and only one (out of 11) community can be classified as a community of senators that support the current government. All other detected communities are not relevant.

Original languageEnglish
Title of host publicationSocial Computing and Social Media. Technologies and Analytics - 10th International Conference, SCSM 2018, Held as Part of HCI International 2018, Proceedings
EditorsGabriele Meiselwitz
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319914848
StatePublished - 2018
Externally publishedYes
Event10th International Conference on Social Computing and Social Media, SCSM 2018 Held as Part of HCI International 2018 - Las Vegas, United States
Duration: 15 Jul 201820 Jul 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10914 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th International Conference on Social Computing and Social Media, SCSM 2018 Held as Part of HCI International 2018
Country/TerritoryUnited States
CityLas Vegas


  • Autoencoder
  • Community detection
  • Convolutional networks
  • Deep learning
  • Text classification


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