{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T18:47:53Z","timestamp":1771699673117,"version":"3.50.1"},"reference-count":59,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2020,8,14]],"date-time":"2020-08-14T00:00:00Z","timestamp":1597363200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Currently, social networks present information of great relevance to various government agencies and different types of companies, which need knowledge insights for their business strategies. From this point of view, an important technique for data analysis is to create and maintain an environment for collecting data and transforming them into intelligence information to enable analysts to observe the evolution of a given topic, elaborate the analysis hypothesis, identify botnets, and generate data to aid in the decision-making process. Focusing on collecting, analyzing, and supporting decision-making, this paper proposes an architecture designed to monitor and perform anonymous real-time searches in tweets to generate information allowing sentiment analysis on a given subject. Therefore, a technological structure and its implementation are defined, followed by processes for data collection and analysis. The results obtained indicate that the proposed solution provides a high capacity to collect, process, search, analyze, and view a large number of tweets in several languages, in real-time, with sentiment analysis capabilities, at a low cost of implementation and operation.<\/jats:p>","DOI":"10.3390\/s20164557","type":"journal-article","created":{"date-parts":[[2020,8,14]],"date-time":"2020-08-14T13:00:18Z","timestamp":1597410018000},"page":"4557","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Anonymous Real-Time Analytics Monitoring Solution for Decision Making Supported by Sentiment Analysis"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6198-4945","authenticated-orcid":false,"given":"Gild\u00e1sio Antonio","family":"de Oliveira J\u00fanior","sequence":"first","affiliation":[{"name":"Cyber Security INCT Unit 6, Laboratory for Decision-Making Technologies (LATITUDE), Department of Electrical Engineering (ENE), Faculty of Technology, University of Bras\u00edlia (UnB), 70910-900 Bras\u00edlia-DF, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6717-3374","authenticated-orcid":false,"given":"Robson","family":"de Oliveira Albuquerque","sequence":"additional","affiliation":[{"name":"Cyber Security INCT Unit 6, Laboratory for Decision-Making Technologies (LATITUDE), Department of Electrical Engineering (ENE), Faculty of Technology, University of Bras\u00edlia (UnB), 70910-900 Bras\u00edlia-DF, Brazil"},{"name":"Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Computer Science and Engineering, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor Jos\u00e9 Garc\u00eda Santesmases 9, Ciudad Universitaria, 28040 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5776-2119","authenticated-orcid":false,"given":"C\u00e9sar Augusto","family":"Borges de Andrade","sequence":"additional","affiliation":[{"name":"Cyber Security INCT Unit 6, Laboratory for Decision-Making Technologies (LATITUDE), Department of Electrical Engineering (ENE), Faculty of Technology, University of Bras\u00edlia (UnB), 70910-900 Bras\u00edlia-DF, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1101-3029","authenticated-orcid":false,"suffix":"Jr.","given":"Rafael Tim\u00f3teo","family":"de Sousa","sequence":"additional","affiliation":[{"name":"Cyber Security INCT Unit 6, Laboratory for Decision-Making Technologies (LATITUDE), Department of Electrical Engineering (ENE), Faculty of Technology, University of Bras\u00edlia (UnB), 70910-900 Bras\u00edlia-DF, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ana Lucila","family":"Sandoval Orozco","sequence":"additional","affiliation":[{"name":"Cyber Security INCT Unit 6, Laboratory for Decision-Making Technologies (LATITUDE), Department of Electrical Engineering (ENE), Faculty of Technology, University of Bras\u00edlia (UnB), 70910-900 Bras\u00edlia-DF, Brazil"},{"name":"Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Computer Science and Engineering, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor Jos\u00e9 Garc\u00eda Santesmases 9, Ciudad Universitaria, 28040 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7573-6272","authenticated-orcid":false,"given":"Luis Javier","family":"Garc\u00eda Villalba","sequence":"additional","affiliation":[{"name":"Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Computer Science and Engineering, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor Jos\u00e9 Garc\u00eda Santesmases 9, Ciudad Universitaria, 28040 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1590\/2318-08892018000100001","article-title":"Prosumers and social networks as marketing information sources. 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