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Using PseudoGravity to Attract People: An Automated Approach to Engaging a Target Audience using Twitter

Lim, SL; Bentley, PJ; (2017) Using PseudoGravity to Attract People: An Automated Approach to Engaging a Target Audience using Twitter. In: Proceedings of the 2017 Future Technologies Conference (FTC). (pp. pp. 515-524). The Science and Information (SAI) Organization Green open access

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Abstract

We introduce the PseudoGravity tool, an automated social media system that establishes a social media presence in the area of interest of a target audience, identifies target users that are open to connect, engages with them, and elicits a complex response and time investment from them. In this work, we use Twitter as the social media platform and an extensive survey as the activity requiring time investment. We evaluate the tool by using it to find and survey a challenging target – science fiction authors – and compare its results with other methods of automated online surveys. In 28 months, the Twitter account managed by the tool achieved more than 12,000 followers, and achieved monthly Tweet Impressions of more than 250,000. The tool also achieved a high survey response rate of 71% and a completion rate of 83% compared to 30% and 47% achieved by typical online surveys, and high numbers of words and characters entered for questions that required free text input. In addition, this work successfully surveyed more than 500 science fiction writers and gained new understandings of the challenges that e-publishing is bringing to their profession.

Type: Proceedings paper
Title: Using PseudoGravity to Attract People: An Automated Approach to Engaging a Target Audience using Twitter
Event: Future Technologies Conference (FTC), 29-30 November 2017, Vancouver, Canada
Location: Vancouver, Canada
Dates: 29 November 2017 - 30 November 2017
ISBN-13: 978-0-9893193-5-5
Open access status: An open access version is available from UCL Discovery
Publisher version: https://saiconference.com/Downloads/FTC2017/Procee...
Language: English
Additional information: This is the published version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Social media, Twitter, artificial intelligence, automated engagement, marketing, online survey, e-publishing
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10057391
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