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What they are Tweeting about me?: social media data analytics with geographical visualisation

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

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What they are Tweeting about me? social media data analytics with geographical visualisation. / Fayoumi, Amjad; Jackson, Christopher; Lewis, Conor et al.
2017.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Harvard

Fayoumi, A, Jackson, C, Lewis, C, Straw, J, Sharpe, J & Nicol, D 2017, 'What they are Tweeting about me? social media data analytics with geographical visualisation'.

APA

Fayoumi, A., Jackson, C., Lewis, C., Straw, J., Sharpe, J., & Nicol, D. (2017). What they are Tweeting about me? social media data analytics with geographical visualisation.

Vancouver

Fayoumi A, Jackson C, Lewis C, Straw J, Sharpe J, Nicol D. What they are Tweeting about me? social media data analytics with geographical visualisation. 2017.

Author

Fayoumi, Amjad ; Jackson, Christopher ; Lewis, Conor et al. / What they are Tweeting about me? social media data analytics with geographical visualisation.

Bibtex

@conference{57fc0b4aa5214a789f301e27e9be1c5c,
title = "What they are Tweeting about me?: social media data analytics with geographical visualisation",
abstract = "In recent years, social media streams have represented vast amounts of insightful information that can be used by organisations to understand market trends and customers{\textquoteright} perceptions and help in making informed strategic decisions. There is an increasing research and development trend toward developing algorithms and tools to analyse such data and support organisations in developing and delivering better services to customers. In this research-in-progress paper, we propose a model for analyzing Twitter data. An initial prototype was developed as a web-based application that allows enterprises to search for specific terms on Twitter; the retrieved results are presented and visualised using the forms of a) a heat-map for geographical distribution, using different colours to highlight the concentration of the Tweets, and b) dashboards using bar graphs. This initial prototype will represent the core engine of future developments in semantic and sentiment social media analysis.",
author = "Amjad Fayoumi and Christopher Jackson and Conor Lewis and Jordon Straw and Joshua Sharpe and Duane Nicol",
year = "2017",
month = mar,
language = "English",

}

RIS

TY - CONF

T1 - What they are Tweeting about me?

T2 - social media data analytics with geographical visualisation

AU - Fayoumi, Amjad

AU - Jackson, Christopher

AU - Lewis, Conor

AU - Straw, Jordon

AU - Sharpe, Joshua

AU - Nicol, Duane

PY - 2017/3

Y1 - 2017/3

N2 - In recent years, social media streams have represented vast amounts of insightful information that can be used by organisations to understand market trends and customers’ perceptions and help in making informed strategic decisions. There is an increasing research and development trend toward developing algorithms and tools to analyse such data and support organisations in developing and delivering better services to customers. In this research-in-progress paper, we propose a model for analyzing Twitter data. An initial prototype was developed as a web-based application that allows enterprises to search for specific terms on Twitter; the retrieved results are presented and visualised using the forms of a) a heat-map for geographical distribution, using different colours to highlight the concentration of the Tweets, and b) dashboards using bar graphs. This initial prototype will represent the core engine of future developments in semantic and sentiment social media analysis.

AB - In recent years, social media streams have represented vast amounts of insightful information that can be used by organisations to understand market trends and customers’ perceptions and help in making informed strategic decisions. There is an increasing research and development trend toward developing algorithms and tools to analyse such data and support organisations in developing and delivering better services to customers. In this research-in-progress paper, we propose a model for analyzing Twitter data. An initial prototype was developed as a web-based application that allows enterprises to search for specific terms on Twitter; the retrieved results are presented and visualised using the forms of a) a heat-map for geographical distribution, using different colours to highlight the concentration of the Tweets, and b) dashboards using bar graphs. This initial prototype will represent the core engine of future developments in semantic and sentiment social media analysis.

M3 - Conference paper

ER -