Public opinion toward social business from a social media perspective

Chien Wen Shen; Jung Tsung Ho

doi:10.1007/978-3-319-93803-5_52

Public opinion toward social business from a social media perspective

Chien Wen Shen, Jung Tsung Ho

Department of Business Administration

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Social media has become a crucial tool used by social businesses (SBs) to manage their public relationships. Hence, understanding what SB means to the public would provide businesses with additional insights that they could apply to social promotion and marketing. We retrieved more than 200,000 tweets containing the words “social business” and utilized text mining algorithms to extract the SB status. The mining results provide marketers with insights that they can apply when making decisions about SB marketing and promotion and provide policymakers with the information necessary to design an SB ecosystem. Our approach contributes a broad view on SB to the literature and differs from conventional methods, such as case studies, surveys, and statistical analyses.

Original language	English
Title of host publication	Data Mining and Big Data - 3rd International Conference, DMBD 2018, Proceedings
Editors	Yuhui Shi, Qirong Tang, Ying Tan
Publisher	Springer Verlag
Pages	555-562
Number of pages	8
ISBN (Print)	9783319938028
DOIs	https://doi.org/10.1007/978-3-319-93803-5_52
State	Published - 2018
Event	3rd International Conference on Data Mining and Big Data, DMBD 2018 held in conjunction with the 9th International Conference on Swarm Intelligence, ICSI 2018 - Shanghai, China Duration: 17 Jun 2018 → 22 Jun 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10943 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Data Mining and Big Data, DMBD 2018 held in conjunction with the 9th International Conference on Swarm Intelligence, ICSI 2018
Country/Territory	China
City	Shanghai
Period	17/06/18 → 22/06/18

Keywords

Social business
Social media
Text mining
Twitter

Access to Document

10.1007/978-3-319-93803-5_52

Cite this

Shen, C. W., & Ho, J. T. (2018). Public opinion toward social business from a social media perspective. In Y. Shi, Q. Tang, & Y. Tan (Eds.), Data Mining and Big Data - 3rd International Conference, DMBD 2018, Proceedings (pp. 555-562). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10943 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-93803-5_52

Shen, Chien Wen ; Ho, Jung Tsung. / Public opinion toward social business from a social media perspective. Data Mining and Big Data - 3rd International Conference, DMBD 2018, Proceedings. editor / Yuhui Shi ; Qirong Tang ; Ying Tan. Springer Verlag, 2018. pp. 555-562 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Social media has become a crucial tool used by social businesses (SBs) to manage their public relationships. Hence, understanding what SB means to the public would provide businesses with additional insights that they could apply to social promotion and marketing. We retrieved more than 200,000 tweets containing the words “social business” and utilized text mining algorithms to extract the SB status. The mining results provide marketers with insights that they can apply when making decisions about SB marketing and promotion and provide policymakers with the information necessary to design an SB ecosystem. Our approach contributes a broad view on SB to the literature and differs from conventional methods, such as case studies, surveys, and statistical analyses.",

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Shen, CW & Ho, JT 2018, Public opinion toward social business from a social media perspective. in Y Shi, Q Tang & Y Tan (eds), Data Mining and Big Data - 3rd International Conference, DMBD 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10943 LNCS, Springer Verlag, pp. 555-562, 3rd International Conference on Data Mining and Big Data, DMBD 2018 held in conjunction with the 9th International Conference on Swarm Intelligence, ICSI 2018, Shanghai, China, 17/06/18. https://doi.org/10.1007/978-3-319-93803-5_52

Public opinion toward social business from a social media perspective. / Shen, Chien Wen; Ho, Jung Tsung.
Data Mining and Big Data - 3rd International Conference, DMBD 2018, Proceedings. ed. / Yuhui Shi; Qirong Tang; Ying Tan. Springer Verlag, 2018. p. 555-562 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10943 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Shen, Chien Wen

AU - Ho, Jung Tsung

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N2 - Social media has become a crucial tool used by social businesses (SBs) to manage their public relationships. Hence, understanding what SB means to the public would provide businesses with additional insights that they could apply to social promotion and marketing. We retrieved more than 200,000 tweets containing the words “social business” and utilized text mining algorithms to extract the SB status. The mining results provide marketers with insights that they can apply when making decisions about SB marketing and promotion and provide policymakers with the information necessary to design an SB ecosystem. Our approach contributes a broad view on SB to the literature and differs from conventional methods, such as case studies, surveys, and statistical analyses.

AB - Social media has become a crucial tool used by social businesses (SBs) to manage their public relationships. Hence, understanding what SB means to the public would provide businesses with additional insights that they could apply to social promotion and marketing. We retrieved more than 200,000 tweets containing the words “social business” and utilized text mining algorithms to extract the SB status. The mining results provide marketers with insights that they can apply when making decisions about SB marketing and promotion and provide policymakers with the information necessary to design an SB ecosystem. Our approach contributes a broad view on SB to the literature and differs from conventional methods, such as case studies, surveys, and statistical analyses.

KW - Social business

KW - Social media

KW - Text mining

KW - Twitter

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T2 - 3rd International Conference on Data Mining and Big Data, DMBD 2018 held in conjunction with the 9th International Conference on Swarm Intelligence, ICSI 2018

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Shen CW, Ho JT. Public opinion toward social business from a social media perspective. In Shi Y, Tang Q, Tan Y, editors, Data Mining and Big Data - 3rd International Conference, DMBD 2018, Proceedings. Springer Verlag. 2018. p. 555-562. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-93803-5_52

Public opinion toward social business from a social media perspective

Abstract

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Keywords

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