Measuring topic network centrality for identifying technology and technological development in online communities
被引:23
作者:
Yang, Zaoli
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机构:
Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R ChinaBeijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
Yang, Zaoli
[1
]
Zhang, Weijian
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机构:
Tianjin 600 Light Year Intelligent Technol Co LTD, Tianjin 3001433, Peoples R ChinaBeijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
Zhang, Weijian
[2
]
Yuan, Fei
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机构:
Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R ChinaBeijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
Yuan, Fei
[1
]
Islam, Nazrul
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机构:
Univ Exeter, Business Sch, Exeter, Devon, EnglandBeijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
Islam, Nazrul
[3
]
机构:
[1] Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
[2] Tianjin 600 Light Year Intelligent Technol Co LTD, Tianjin 3001433, Peoples R China
[3] Univ Exeter, Business Sch, Exeter, Devon, England
Online communities are a rapidly growing knowledge repository that provides scholarly research, technical discussion, and social interactivity. This abundance of online information increases the difficulty of keeping up with new developments difficult for researchers and practitioners. Thus, we introduced a novel method that analyses both knowledge and social sentiment within the online community to discover the topical coverage of emerging technology and trace technological trends. The method utilizes the Weibull distribution and Shannon entropy to measure and link social sentiment with technological topics. Based on question-and-answer and social sentiment data from Zhihu, which is an online question and answer (Q&A) community with high-profile entrepreneurs and public intellectuals, we built an undirected weighting network and measured the centrality of nodes for technology identification. An empirical study on artificial intelligence technology trends supported by expert knowledge-based evaluation and cognition provides sufficient evidence of the method's ability to identify technology. We found that the social sentiment of hot technological topics presents a long-tailed distribution statistical pattern. High similarity between the topic popularity and emerging technology development trends appears in the online community. Finally, we discuss the findings in various professional fields that are widely applied to discover and track hot technological topics.
机构:
Yonsei Univ, Dept Informat & Ind Engn, 134 Shinchon Dong, Seoul 120749, South KoreaYonsei Univ, Dept Informat & Ind Engn, 134 Shinchon Dong, Seoul 120749, South Korea
Kim, Tae San
;
Sohn, So Young
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机构:
Yonsei Univ, Dept Informat & Ind Engn, 134 Shinchon Dong, Seoul 120749, South KoreaYonsei Univ, Dept Informat & Ind Engn, 134 Shinchon Dong, Seoul 120749, South Korea
机构:
Chinese Acad Sci, Chengdu Lib, Chengdu 610041, Sichuan, Peoples R China
Chinese Acad Sci, Informat Ctr, Chengdu 610041, Sichuan, Peoples R ChinaChinese Acad Sci, Chengdu Lib, Chengdu 610041, Sichuan, Peoples R China
Li, Shuying
;
Garces, Edwin
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机构:
Portland State Univ, Dept Engn & Technol Management, Portland, OR 97207 USAChinese Acad Sci, Chengdu Lib, Chengdu 610041, Sichuan, Peoples R China
机构:
Yonsei Univ, Dept Informat & Ind Engn, 134 Shinchon Dong, Seoul 120749, South KoreaYonsei Univ, Dept Informat & Ind Engn, 134 Shinchon Dong, Seoul 120749, South Korea
Kim, Tae San
;
Sohn, So Young
论文数: 0引用数: 0
h-index: 0
机构:
Yonsei Univ, Dept Informat & Ind Engn, 134 Shinchon Dong, Seoul 120749, South KoreaYonsei Univ, Dept Informat & Ind Engn, 134 Shinchon Dong, Seoul 120749, South Korea
机构:
Chinese Acad Sci, Chengdu Lib, Chengdu 610041, Sichuan, Peoples R China
Chinese Acad Sci, Informat Ctr, Chengdu 610041, Sichuan, Peoples R ChinaChinese Acad Sci, Chengdu Lib, Chengdu 610041, Sichuan, Peoples R China
Li, Shuying
;
Garces, Edwin
论文数: 0引用数: 0
h-index: 0
机构:
Portland State Univ, Dept Engn & Technol Management, Portland, OR 97207 USAChinese Acad Sci, Chengdu Lib, Chengdu 610041, Sichuan, Peoples R China