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Social media analytics system for action inspection on social networks
Social networks are increasingly used for discussing all kinds of topics, including those related to politics, serving as a virtual arena. Consequently, analysing online conversations, for example, to predict election outcomes, is becoming a popular and challenging research area. On social networkin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Vienna
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818504/ https://www.ncbi.nlm.nih.gov/pubmed/35154503 http://dx.doi.org/10.1007/s13278-021-00853-w |
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author | Mameli, Marco Paolanti, Marina Morbidoni, Christian Frontoni, Emanuele Teti, Antonio |
author_facet | Mameli, Marco Paolanti, Marina Morbidoni, Christian Frontoni, Emanuele Teti, Antonio |
author_sort | Mameli, Marco |
collection | PubMed |
description | Social networks are increasingly used for discussing all kinds of topics, including those related to politics, serving as a virtual arena. Consequently, analysing online conversations, for example, to predict election outcomes, is becoming a popular and challenging research area. On social networking sites, citizens express themselves spontaneously regarding political topics, often driven by specific events in social life. Real-time analysis of social media can provide valuable feedback and insights to both politicians and news agencies. In this paper, we discuss the design and implementation of a system for tracking and analysing social media. The SocMINT system provides an easy-to-use, visual dashboard to monitor the discussion on specific topics, to capture trends in communities and, by iteratively applying multidimensional data analysis and filtering, to deeply analyse posts and influencers. SocMINT aggregates data from multiple social sources and performs sentiment analysis on textual, visual and mixed content via a specifically designed neural network architecture. The system was applied in a real context by administrative staff of a political party to effectively analyse candidates’ political communication on Facebook, Instagram and Twitter and the related online community reactions and discussion. In the paper, we report on this real-world case study, showing how the system meaningfully captures trends in public opinion, comparing the main KPIs provided by SocMINT with the outcomes of traditional polls. |
format | Online Article Text |
id | pubmed-8818504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Vienna |
record_format | MEDLINE/PubMed |
spelling | pubmed-88185042022-02-07 Social media analytics system for action inspection on social networks Mameli, Marco Paolanti, Marina Morbidoni, Christian Frontoni, Emanuele Teti, Antonio Soc Netw Anal Min Original Article Social networks are increasingly used for discussing all kinds of topics, including those related to politics, serving as a virtual arena. Consequently, analysing online conversations, for example, to predict election outcomes, is becoming a popular and challenging research area. On social networking sites, citizens express themselves spontaneously regarding political topics, often driven by specific events in social life. Real-time analysis of social media can provide valuable feedback and insights to both politicians and news agencies. In this paper, we discuss the design and implementation of a system for tracking and analysing social media. The SocMINT system provides an easy-to-use, visual dashboard to monitor the discussion on specific topics, to capture trends in communities and, by iteratively applying multidimensional data analysis and filtering, to deeply analyse posts and influencers. SocMINT aggregates data from multiple social sources and performs sentiment analysis on textual, visual and mixed content via a specifically designed neural network architecture. The system was applied in a real context by administrative staff of a political party to effectively analyse candidates’ political communication on Facebook, Instagram and Twitter and the related online community reactions and discussion. In the paper, we report on this real-world case study, showing how the system meaningfully captures trends in public opinion, comparing the main KPIs provided by SocMINT with the outcomes of traditional polls. Springer Vienna 2022-02-07 2022 /pmc/articles/PMC8818504/ /pubmed/35154503 http://dx.doi.org/10.1007/s13278-021-00853-w Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Mameli, Marco Paolanti, Marina Morbidoni, Christian Frontoni, Emanuele Teti, Antonio Social media analytics system for action inspection on social networks |
title | Social media analytics system for action inspection on social networks |
title_full | Social media analytics system for action inspection on social networks |
title_fullStr | Social media analytics system for action inspection on social networks |
title_full_unstemmed | Social media analytics system for action inspection on social networks |
title_short | Social media analytics system for action inspection on social networks |
title_sort | social media analytics system for action inspection on social networks |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818504/ https://www.ncbi.nlm.nih.gov/pubmed/35154503 http://dx.doi.org/10.1007/s13278-021-00853-w |
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