Big Data-driven Social Media Management

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    IRIS: Learning the Underlying Information of Scientific Research Interests Using Heterogeneous Network Representation
    ( 2022-01-04) Feng, Zihan ; Cui, Hongfei
    Understanding scientific research fields and finding potential relations between seemingly distinct fields can help researchers rapidly grasp their most interested topics with expertises. In this study, we construct a heterogeneous network which contains authors, keywords, papers and institutions, and built an “Integrated Research Interest Space (IRIS)” which can represent both author and keyword nodes. Similar keywords in the sense of research interest and research manner can obvious aggregate together. Authors that are interested in different keywords distributed in different IRIS areas, with strongly associated with research objectives and methodologies of the keywords. The average similarities between authors and their real used keywords is significantly higher than that of randomly chosen author-keyword pairs. Based on these observations, we propose a simple algorithm which attempts to recommend potential interested keywords for researchers, and got meaningful results. Our study may also give useful hints for understanding research interests and discovering potential cross disciplines.
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    Exploring the Influencing Factors of IP Film Rating by Sentiment Analysis and GMM
    ( 2022-01-04) Ma, Yingxue ; Gan, Mingxin ; Xv, Jiao
    Recently, intellectual property (IP) film has become an important accessory for entertainment, and its rating has become the focus of quality evaluation. However, existing research seldom conducts study on influencing factors of rating. In this paper, we use sentiment analysis and generalized method of moments (GMM) to explore the factors that affect IP film rating. We take advantage of production, broadcast, genre and audience feedback to construct six explanatory variables, including actor influence, screenwriter participation, broadcast time, broadcast platform, genre, and adaptation satisfaction. We use LLC, IPS and Sargan tests to conduct variable stability test and model setting test. From the regression results of 134 IP films that obtained by sample filtering, the impact of each influencing factor on the rating is obtained. We found that short-term historical rating, actor influence, adaptation satisfaction and screenwriter participation positively affect current rating. While, long-term historical rating has a negative impact on current rating. In addition, broadcast time and broadcast platform have imposed positive impact on IP film rating, and genre has only a weak impact on rating. Our work provides advice for IP film producers, prompting them to improve quality by emphasizing celebrity effects and author participation.
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    Data-driven Analysis of Remote Work in China during the COVID-19 Pandemic
    ( 2022-01-04) Wu, Yufei ; Munasinghe, Thilanka ; Manikonda, Lydia ; Seneviratne, Oshani
    This paper leverages online content to investigate teleworking forced due to the COVID-19 pandemic -- using China as a primary case study. Telecommuting has become popular since February 2020 primarily due to the pandemic, and people have been slowly returning to their office from May 2020. This study focuses on two time windows in the year 2020 to calculate the growth of different job sectors. Our results indicate the negative impact of teleworking in manufacturing industry, but shows that information technology-related industries are less affected by working from home. This paper also investigates the impact of COVID-19 on the stock market and discussed what plan of action the policy-makers should take to provide a good economic environment. In addition to the overall economic situation, the psychological situation of employees will affect the development of a given industry. Therefore, misinformation in certain Chinese social media channels is also a concern studied in this paper specifically examining the rumors and their latent topics. We hope that our work will initiate a dialogue and collaboration between scientists, policy makers and government officials to use these lessons and engage effectively for the betterment of society.
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