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      Identifying critical outbreak time window of controversial events based on sentiment analysis

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      PLoS ONE
      Public Library of Science

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          Abstract

          The response of netizens toward controversial events plays an important guiding role in the development of events. Based on the identification of such responses, this study aimed to determine the critical outbreak time window of events. The microblog texts related to an event were divided into seven emotional categories via multi-emotional analysis to capture the subtle emotions of netizens toward an event, i.e., public opinion. By detecting the characteristics of the text and regional coverage of emotions, an emotional coverage index that reflects the intensity of emotional impact was proposed to determine the mainstream emotion of netizens. By capturing the mutation characteristics of the impact intensity of mainstream emotions, the critical time window of the public opinion toward the event was obtained. The experimental results demonstrated that the proposed method can effectively identify the critical outbreak time window of controversial events, which can help authorities in preventing the further aggravation of events.

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          Most cited references60

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          Social media? Get serious! Understanding the functional building blocks of social media

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            Affective Computing and Sentiment Analysis

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              Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter

              , , (2011)
              Individual happiness is a fundamental societal metric. Normally measured through self-report, happiness has often been indirectly characterized and overshadowed by more readily quantifiable economic indicators such as gross domestic product. Here, we examine expressions made on the online, global microblog and social networking service Twitter, uncovering and explaining temporal variations in happiness and information levels over timescales ranging from hours to years. Our data set comprises over 46 billion words contained in nearly 4.6 billion expressions posted over a 33 month span by over 63 million unique users. In measuring happiness, we use a real-time, remote-sensing, non-invasive, text-based approach---a kind of hedonometer. In building our metric, made available with this paper, we conducted a survey to obtain happiness evaluations of over 10,000 individual words, representing a tenfold size improvement over similar existing word sets. Rather than being ad hoc, our word list is chosen solely by frequency of usage and we show how a highly robust metric can be constructed and defended.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Writing – original draft
                Role: InvestigationRole: Visualization
                Role: Visualization
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                29 October 2020
                2020
                : 15
                : 10
                : e0241355
                Affiliations
                [1 ] College of Information and Computer Engineering, Northeast Forestry University, Harbin, People’s Republic of China
                [2 ] Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, People’s Republic of China
                Universitat de Barcelona, SPAIN
                Author notes

                Competing Interests: SZ was affiliated with Asia Intelligence Technology Pte Ltd during the research period. There are no patents, products in development or marketed products associated with this research to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials. The authors have declared that no other competing interests exist.

                Author information
                https://orcid.org/0000-0003-0525-6120
                Article
                PONE-D-19-26249
                10.1371/journal.pone.0241355
                7595406
                33119686
                13eaf90a-5503-43cb-9c4d-4658ab0dbf9a
                © 2020 Wang et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 September 2019
                : 5 October 2020
                Page count
                Figures: 9, Tables: 4, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 71473034
                Award Recipient :
                Funded by: Heilongjiang Provincial Natural Science Foundation of China
                Award ID: LH2019G001
                Award Recipient :
                Funded by: Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province
                Award ID: LBH-Q16003
                Award Recipient :
                This work was supported by the National Natural Science Foundation of China (Grant No. 71473034), the Heilongjiang Provincial Natural Science Foundation of China (Grant No. LH2019G001), and the financial assistance from Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province (Grant No. LBH-Q16003). All the funds were obtained by MW. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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                All relevant data are within the manuscript and its Supporting Information files.

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