A Review on MAS-Based Sentiment and Stress Analysis User-Guiding and Risk-Prevention Systems in Social Network Analysis
| Autor: | Vicente J. Julián Inglada, Ana García-Fornes, Guillem Aguado-Sarrió, Agustín Rafael Espinosa Minguet |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
social networks
Computer science Stress analysis 02 engineering and technology lcsh:Technology Social networks Stress level lcsh:Chemistry Sentiment analysis 020204 information systems Stress (linguistics) 0202 electrical engineering electronic engineering information engineering General Materials Science lcsh:QH301-705.5 Instrumentation Social network analysis Fluid Flow and Transfer Processes Multi-Agent System Social network lcsh:T business.industry Process Chemistry and Technology Multi-agent system General Engineering Data science lcsh:QC1-999 Social relation Computer Science Applications lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 sentiment analysis stress analysis 020201 artificial intelligence & image processing Risk prevention lcsh:Engineering (General). Civil engineering (General) business LENGUAJES Y SISTEMAS INFORMATICOS lcsh:Physics |
| Zdroj: | Applied Sciences Volume 10 Issue 19 RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname Applied Sciences, Vol 10, Iss 6746, p 6746 (2020) |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app10196746 |
| Popis: | [EN] In the current world we live immersed in online applications, being one of the most present of them Social Network Sites (SNSs), and different issues arise from this interaction. Therefore, there is a need for research that addresses the potential issues born from the increasing user interaction when navigating. For this reason, in this survey we explore works in the line of prevention of risks that can arise from social interaction in online environments, focusing on works using Multi-Agent System (MAS) technologies. For being able to assess what techniques are available for prevention, works in the detection of sentiment polarity and stress levels of users in SNSs will be reviewed. We review with special attention works using MAS technologies for user recommendation and guiding. Through the analysis of previous approaches on detection of the user state and risk prevention in SNSs we elaborate potential future lines of work that might lead to future applications where users can navigate and interact between each other in a more safe way. This work was funded by the project TIN2017-89156-R of the Spanish government. |
| Databáze: | OpenAIRE |
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