Use of a High-Value Social Audience index for target audience identification on Twitter

Siaw Ling Lo; David Cornforth; Raymond Chiong

doi:10.1007/978-3-319-14803-8_25

Use of a High-Value Social Audience index for target audience identification on Twitter

Siaw Ling Lo
, David Cornforth
, Raymond Chiong

School of Science & Technology

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

5 Citations (Scopus)

Abstract

With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. This is mainly due to the challenge of extracting commercially viable contents from the vast amount of free-form conversations. In this paper, we analyse the Twitter content of an account owner and its list of followers through various text mining methods and segment the list of followers via an index. We have termed this index as the High-Value Social Audience (HVSA) index. This HVSA index enables a company or organisation to devise their marketing and engagement plan according to available resources, so that a high-value social audience can potentially be transformed to customers, and hence improve the return on investment.

Original language	English
Title of host publication	Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings
Editors	Stephan K. Chalup, Alan D. Blair, Marcus Randall
Place of Publication	Switzerland
Publisher	Springer
Pages	323-336
ISBN (Print)	9783319148038, 9783319148021
DOIs	https://doi.org/10.1007/978-3-319-14803-8_25
Publication status	Published - 2015
Event	ACALCI 2015: Artificial Life and Computational Intelligence - Newcastle, Australia Duration: 5 Feb 2015 → 7 Feb 2015

Conference

Conference	ACALCI 2015: Artificial Life and Computational Intelligence
Country/Territory	Australia
City	Newcastle
Period	5/02/15 → 7/02/15

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10.1007/978-3-319-14803-8_25

https://hdl.handle.net/1959.11/61488

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Lo, S. L., Cornforth, D., & Chiong, R. (2015). Use of a High-Value Social Audience index for target audience identification on Twitter. In S. K. Chalup, A. D. Blair, & M. Randall (Eds.), Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings (pp. 323-336). Springer. https://doi.org/10.1007/978-3-319-14803-8_25

Lo, Siaw Ling ; Cornforth, David ; Chiong, Raymond. / Use of a High-Value Social Audience index for target audience identification on Twitter. Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings. editor / Stephan K. Chalup ; Alan D. Blair ; Marcus Randall. Switzerland : Springer, 2015. pp. 323-336

@inproceedings{1e496a57162944de891712e500ff1f90,

title = "Use of a High-Value Social Audience index for target audience identification on Twitter",

abstract = "With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. This is mainly due to the challenge of extracting commercially viable contents from the vast amount of free-form conversations. In this paper, we analyse the Twitter content of an account owner and its list of followers through various text mining methods and segment the list of followers via an index. We have termed this index as the High-Value Social Audience (HVSA) index. This HVSA index enables a company or organisation to devise their marketing and engagement plan according to available resources, so that a high-value social audience can potentially be transformed to customers, and hence improve the return on investment.",

author = "Lo, \{Siaw Ling\} and David Cornforth and Raymond Chiong",

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editor = "Chalup, \{Stephan K.\} and Blair, \{Alan D.\} and Marcus Randall",

booktitle = "Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings",

publisher = "Springer",

note = "ACALCI 2015: Artificial Life and Computational Intelligence ; Conference date: 05-02-2015 Through 07-02-2015",

}

Lo, SL, Cornforth, D & Chiong, R 2015, Use of a High-Value Social Audience index for target audience identification on Twitter. in SK Chalup, AD Blair & M Randall (eds), Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings. Springer, Switzerland, pp. 323-336, ACALCI 2015: Artificial Life and Computational Intelligence, Newcastle, New South Wales, Australia, 5/02/15. https://doi.org/10.1007/978-3-319-14803-8_25

Use of a High-Value Social Audience index for target audience identification on Twitter. / Lo, Siaw Ling; Cornforth, David; Chiong, Raymond.
Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings. ed. / Stephan K. Chalup; Alan D. Blair; Marcus Randall. Switzerland: Springer, 2015. p. 323-336.

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

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AU - Lo, Siaw Ling

AU - Cornforth, David

AU - Chiong, Raymond

PY - 2015

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N2 - With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. This is mainly due to the challenge of extracting commercially viable contents from the vast amount of free-form conversations. In this paper, we analyse the Twitter content of an account owner and its list of followers through various text mining methods and segment the list of followers via an index. We have termed this index as the High-Value Social Audience (HVSA) index. This HVSA index enables a company or organisation to devise their marketing and engagement plan according to available resources, so that a high-value social audience can potentially be transformed to customers, and hence improve the return on investment.

AB - With the large and growing user base of social media, it is not an easy feat to identify potential customers for business. This is mainly due to the challenge of extracting commercially viable contents from the vast amount of free-form conversations. In this paper, we analyse the Twitter content of an account owner and its list of followers through various text mining methods and segment the list of followers via an index. We have termed this index as the High-Value Social Audience (HVSA) index. This HVSA index enables a company or organisation to devise their marketing and engagement plan according to available resources, so that a high-value social audience can potentially be transformed to customers, and hence improve the return on investment.

U2 - 10.1007/978-3-319-14803-8_25

DO - 10.1007/978-3-319-14803-8_25

M3 - Conference contribution

SN - 9783319148038

SN - 9783319148021

SP - 323

EP - 336

BT - Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings

A2 - Chalup, Stephan K.

A2 - Blair, Alan D.

A2 - Randall, Marcus

PB - Springer

CY - Switzerland

T2 - ACALCI 2015: Artificial Life and Computational Intelligence

Y2 - 5 February 2015 through 7 February 2015

ER -

Lo SL, Cornforth D, Chiong R. Use of a High-Value Social Audience index for target audience identification on Twitter. In Chalup SK, Blair AD, Randall M, editors, Artificial Life and Computational Intelligence, First Australasian Conference, ACALCI 2015, Newcastle, NSW, Australia, February 5-7, 2015, Proceedings. Switzerland: Springer. 2015. p. 323-336 doi: 10.1007/978-3-319-14803-8_25

Use of a High-Value Social Audience index for target audience identification on Twitter

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