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      Identifying long-term periodic cycles and memories of collective emotion in online social media

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          Abstract

          Collective emotion has been traditionally evaluated by questionnaire survey on a limited number of people. Recently, big data of written texts on the Internet has been available for analyzing collective emotion for very large scales. Although short-term reflection between collective emotion and real social phenomena has been widely studied, long-term dynamics of collective emotion has not been studied so far due to the lack of long persistent data sets. In this study, we extracted collective emotion over a 10-year period from 3.6 billion Japanese blog articles. Firstly, we find that collective emotion shows clear periodic cycles, i.e., weekly and seasonal behaviors, accompanied with pulses caused by natural disasters. For example, April is represented by high Tension, probably due to starting school in Japan. We also identified long-term memory in the collective emotion that is characterized by the power-law decay of the autocorrelation function over several months.

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          Most cited references 23

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          Experimental evidence of massive-scale emotional contagion through social networks.

          Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks [Fowler JH, Christakis NA (2008) BMJ 337:a2338], although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others' positive experiences constitutes a positive experience for people.
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            Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures.

             S Golder,  M Macy (2011)
            We identified individual-level diurnal and seasonal mood rhythms in cultures across the globe, using data from millions of public Twitter messages. We found that individuals awaken in a good mood that deteriorates as the day progresses--which is consistent with the effects of sleep and circadian rhythm--and that seasonal change in baseline positive affect varies with change in daylength. People are happier on weekends, but the morning peak in positive affect is delayed by 2 hours, which suggests that people awaken later on weekends.
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              Is Open Access

              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: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2019
                21 March 2019
                : 14
                : 3
                Affiliations
                [1 ] Department of Policy and Planning Sciences, University of Tsukuba, Ibaraki, Japan
                [2 ] Sony Computer Science Laboratories, Inc., Tokyo, Japan
                [3 ] Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
                [4 ] Department of Physics, Bar-Ilan University, Ramat-Gan, Israel
                University of Warwick, UNITED KINGDOM
                Author notes

                Competing Interests: We have the following interests. Hideki Takayasu is employed by Sony Computer Science Laboratories, Inc. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.

                Article
                PONE-D-18-23596
                10.1371/journal.pone.0213843
                6428299
                30897174
                © 2019 Sano 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.

                Page count
                Figures: 5, Tables: 2, Pages: 17
                Product
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100009036, Strategic International Collaborative Research Program;
                Award ID: Japan-Israel Cooperative Scientific Research on ICT for a Resilient Society
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001691, Japan Society for the Promotion of Science;
                Award ID: 17K12783
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003050, Ministry of Economy, Trade and Industry;
                Award ID: Development Project of New Indicators Utilizing Big Data and its Analysis Technology
                Award Recipient :
                This work was supported by JST and MOST, SICORP Japan-Israel Cooperative Scientific Research on ICT for a Resilient Society (YS, HT, SH, MT) and METI Development Project of New Indicators Utilizing Big Data and its Analysis Technology (YS, HT, MT). This work was partially supported by JSPS KAKENHI Grant Number 17K12783 (YS). There was no additional external funding received for this study. Sony Computer Science Laboratories, Inc. provided support in the form of salaries for author HT, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of HT is given in the ‘author contributions’ section.
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