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Thomas W Jackson

Biographic Data

ID355933
NAMEThomas W Jackson
GIVEN NAMESThomas W
FAMILY NAMEJackson
SIGNATUREJACKSON T W
AFFILIATIONSLoughborough University
VERIFIEDNo
TOTAL WORKS4
TOTAL CITATIONS6
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR1986
LATEST PUBLICATION YEAR2020
H-INDEX1
  • A qualitative analysis of sarcasm, irony and related #hashtags on Twitter

    Open Access•Martin Sykora, Suzanne Elayan et al.•ARTICLE•Big Data & Society•2020•Cited by: 6•References: 44

    As the use of automated social media analysis tools surges, concerns over accuracy of analytics have increased. Some tentative evidence suggests that sarcasm alone could account for as much as a 50% drop in accuracy when automatically detecting sentiment. This paper assesses and outlines the prevalence of sarcastic and ironic language within social media posts. Several past studies proposed models for automatic sarcasm and irony detection for sen…

  • Empirical evaluation of a technology acceptance model for mobile policing

    Rachael Lindsay, Thomas W Jackson et al.•ARTICLE•Police Practice and Research•2014

    Technology acceptance in policing is under-researched, yet mobile devices are widely implemented across UK police forces. The paper validates a mobile technology acceptance model (M-TAM) developed in a single police force. It shows that the M-TAM is transferrable to other UK police forces, and potentially worldwide. The influence of local supervision and fit of technology to roles and tasks are shown to be the most influential factors. Factors be…

  • On a Slow Train through Arkansaw

    Timothy P Donovan, Thomas W Jackson et al.•ARTICLE•The Arkansas Historical Quarterly•1986

  • Vance Randolph. An Ozark Life

    Open Access•William M Clements, Robert Cochran et al.•ARTICLE•Western Folklore•1986

  • A qualitative analysis of sarcasm, irony and related #hashtags on Twitter

    Open Access•Martin Sykora, Suzanne Elayan et al.•ARTICLE•Big Data & Society•2020•Cited by: 6•References: 44

    As the use of automated social media analysis tools surges, concerns over accuracy of analytics have increased. Some tentative evidence suggests that sarcasm alone could account for as much as a 50% drop in accuracy when automatically detecting sentiment. This paper assesses and outlines the prevalence of sarcastic and ironic language within social media posts. Several past studies proposed models for automatic sarcasm and irony detection for sen…

  • On a Slow Train through Arkansaw

    Timothy P Donovan, Thomas W Jackson et al.•ARTICLE•The Arkansas Historical Quarterly•1986

  • Vance Randolph. An Ozark Life

    Open Access•William M Clements, Robert Cochran et al.•ARTICLE•Western Folklore•1986

  • Empirical evaluation of a technology acceptance model for mobile policing

    Rachael Lindsay, Thomas W Jackson et al.•ARTICLE•Police Practice and Research•2014

    Technology acceptance in policing is under-researched, yet mobile devices are widely implemented across UK police forces. The paper validates a mobile technology acceptance model (M-TAM) developed in a single police force. It shows that the M-TAM is transferrable to other UK police forces, and potentially worldwide. The influence of local supervision and fit of technology to roles and tasks are shown to be the most influential factors. Factors be…

  • A qualitative analysis of sarcasm, irony and related #hashtags on Twitter

    Open Access•Martin Sykora, Suzanne Elayan et al.•ARTICLE•Big Data & Society•2020•Cited by: 6•References: 44

    As the use of automated social media analysis tools surges, concerns over accuracy of analytics have increased. Some tentative evidence suggests that sarcasm alone could account for as much as a 50% drop in accuracy when automatically detecting sentiment. This paper assesses and outlines the prevalence of sarcastic and ironic language within social media posts. Several past studies proposed models for automatic sarcasm and irony detection for sen…

Computer Science (2 works) · World Wide Web (2 works) · Advanced Text Analysis Techniques (1 works) · Annotation (1 works) · Archaeology (1 works) · Art (1 works) · Artificial Intelligence (1 works) · Business (1 works) · Data science (1 works) · Digital Marketing and Social Media (1 works)

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