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A Normalized Rich-Club Connectivity-Based Strategy for Keyword Selection in Social Media Analysis

Author

Listed:
  • Ying Lian

    (School of Journalism, Communication University of China, Beijing 100024, China)

  • Xiaofeng Lin

    (Center for Innovation-Driven Development (Center for Digital Economy Research and Development), National Development and Reform Commission, Beijing 100045, China)

  • Xuefan Dong

    (College of Economics and Management, Beijing University of Technology, Beijing 100124, China
    Research Base of Beijing Modern Manufacturing Development, Beijing University of Technology, Beijing 100124, China)

  • Shengjie Hou

    (National Innovation Institute of Defense Technology, Beijing 100071, China)

Abstract

In this paper, we present a study on keyword selection behavior in social media analysis that is focused on particular topics, and propose a new effective strategy that considers the co-occurrence relationships between keywords and uses graph-based techniques. In particular, we used the normalized rich-club connectivity considering the weighted degree, closeness centrality, betweenness centrality and PageRank values to measure a subgroup of highly connected “rich keywords” in a keyword co-occurrence network. Community detection is subsequently applied to identify several keyword combinations that are able to accurately and comprehensively represent the researched topic. The empirical results based on four topics and comparing four existing models confirm the performance of our proposed strategy in promoting the quantity and ensuing the quality of data related to particular topics collected from social media. Overall, our findings are expected to offer useful guidelines on how to select keywords for social media-based studies and thus further increase the reliability and validity of their respective conclusions.

Suggested Citation

  • Ying Lian & Xiaofeng Lin & Xuefan Dong & Shengjie Hou, 2022. "A Normalized Rich-Club Connectivity-Based Strategy for Keyword Selection in Social Media Analysis," Sustainability, MDPI, vol. 14(13), pages 1-19, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7722-:d:846914
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    References listed on IDEAS

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    1. Subhajyoti Samaddar & Sudip Roy & Fatima Akter & Hirokazu Tatano, 2022. "Diffusion of Disaster-Preparedness Information by Hearing from Early Adopters to Late Adopters in Coastal Bangladesh," Sustainability, MDPI, vol. 14(7), pages 1-19, March.
    2. Lian, Ying & Liu, Yijun & Dong, Xuefan, 2020. "Strategies for controlling false online information during natural disasters: The case of Typhoon Mangkhut in China," Technology in Society, Elsevier, vol. 62(C).
    3. Lian, Ying & Dong, Xuefan & Liu, Yijun, 2017. "Topological evolution of the internet public opinion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 567-578.
    4. Jin, Haiyan & Zhang, ChenXing & Ma, Mengzhou & Gong, Qianhua & Yu, Liang & Guo, Xingli & Gao, Lin & Wang, Bingbo, 2020. "Inferring essential proteins from centrality in interconnected multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    5. Smilkov, Daniel & Kocarev, Ljupco, 2010. "Rich-club and page-club coefficients for directed graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(11), pages 2290-2299.
    6. Qikai Cheng & Jiamin Wang & Wei Lu & Yong Huang & Yi Bu, 2020. "Keyword-citation-keyword network: a new perspective of discipline knowledge structure analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1923-1943, September.
    7. Anik, Md Asif Hasan & Sadeek, Soumik Nafis & Hossain, Moinul & Kabir, Shafquat, 2020. "A framework for involving the young generation in transportation planning using social media and crowd sourcing," Transport Policy, Elsevier, vol. 97(C), pages 1-18.
    8. Lu, Wei & Liu, Zhifeng & Huang, Yong & Bu, Yi & Li, Xin & Cheng, Qikai, 2020. "How do authors select keywords? A preliminary study of author keyword selection behavior," Journal of Informetrics, Elsevier, vol. 14(4).
    9. Behrouzi, Saman & Shafaeipour Sarmoor, Zahra & Hajsadeghi, Khosrow & Kavousi, Kaveh, 2020. "Predicting scientific research trends based on link prediction in keyword networks," Journal of Informetrics, Elsevier, vol. 14(4).
    10. Sarah Kaplan & Keyvan Vakili, 2015. "The double-edged sword of recombination in breakthrough innovation," Strategic Management Journal, Wiley Blackwell, vol. 36(10), pages 1435-1457, October.
    11. Abu Elnasr E. Sobaih & Ahmed Hasanein & Ibrahim A. Elshaer, 2022. "Higher Education in and after COVID-19: The Impact of Using Social Network Applications for E-Learning on Students’ Academic Performance," Sustainability, MDPI, vol. 14(9), pages 1-12, April.
    12. Lyu, YuWen & Chow, Julian Chun-Chung & Hwang, Ji-Jen, 2020. "Exploring public attitudes of child abuse in mainland China: A sentiment analysis of China’s social media Weibo," Children and Youth Services Review, Elsevier, vol. 116(C).
    13. Anna Shutaleva & Nikita Martyushev & Zhanna Nikonova & Irina Savchenko & Sofya Abramova & Vladlena Lubimova & Anastasia Novgorodtseva, 2021. "Environmental Behavior of Youth and Sustainable Development," Sustainability, MDPI, vol. 14(1), pages 1-26, December.
    14. Ren, Tao & Wang, Yi-fan & Du, Dan & Liu, Miao-miao & Siddiqi, Awais, 2016. "The guitar chord-generating algorithm based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 1-13.
    15. Xicheng Yin & Hongwei Wang & Pei Yin & Hengmin Zhu & Zhenyu Zhang, 2020. "A co-occurrence based approach of automatic keyword expansion using mass diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1885-1905, September.
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