Professor of Information Systems, University of Bath

Adam Joinson holds the post of ‘Professor of Information Systems' at the University of Bath, School of Management. 

His research focuses on the interaction between psychology and technology, with a particular focus on how technology can shape behaviour, social relations and attitudes. Adam leads the Understanding And Countering Online Behaviour programme at CREST.



What demographic attributes do our digital footprints reveal? A systematic review

To what extent does our online activity reveal who we are? Recent research has demonstrated that the digital traces left by individuals as they browse and interact with others online may reveal who they are and what their interests may be. In the present paper we report a systematic review that synthesises current evidence on predicting demographic attributes from online digital traces. Studies were included if they met the following criteria: (i) they reported findings where at least one demographic attribute was predicted/inferred from at least one form of digital footprint, (ii) the method of prediction was automated, and (iii) the traces were either visible (e.g. tweets) or non-visible (e.g. clickstreams). We identified 327 studies published up until October 2018. Across these articles, 14 demographic attributes were successfully inferred from digital traces; the most studied included gender, age, location, and political orientation. For each of the demographic attributes identified, we provide a database containing the platforms and digital traces examined, sample sizes, accuracy measures and the classification methods applied. Finally, we discuss the main research trends/findings, methodological approaches and recommend directions for future research.

(From the journal abstract)

Hinds, J., & Joinson, A. N. (2018). What demographic attributes do our digital footprints reveal? A systematic review. PLOS ONE, 13(11), e0207112.

Authors: Joanne Hinds, Adam Joinson
Characterizing the Linguistic Chameleon: Personal and Social Correlates of Linguistic Style Accommodation

Linguistic style accommodation between conversationalists is associated with positive social outcomes. We examine social power and personality as factors driving the occurrence of linguistic style accommodation, and the social outcomes of accommodation. Social power was manipulated to create 144 face-to-face dyadic interactions between individuals of high versus low power and 64 neutral power interactions. Particular configurations of personality traits (high self-monitoring, Machiavellianism and leadership, and low self-consciousness, impression management and agreeableness), combined with a low-power role, led to an increased likelihood of linguistic style accommodation. Further, greater accommodation by low-power individuals positively influenced perceptions of subjective rapport and attractiveness. We propose individual differences interact with social context to influence the conditions under which nonconscious communication accommodation occurs.

(From the journal abstract)

Muir, K., Joinson, A., Cotterill, R., & Dewdney, N. (2016). Characterizing the Linguistic Chameleon: Personal and Social Correlates of Linguistic Style Accommodation: Characterizing the Linguistic Chameleon. Human Communication Research, 42(3), 462–484.

Authors: Kate Muir, Adam Joinson
The Rise of Consumer Health Wearables: Promises and Barriers

Will consumer wearable technology ever be adopted or accepted by the medical community? Patients and practitioners regularly use digital technology (e.g., thermometers and glucose monitors) to identify and discuss symptoms. In addition, a third of general practitioners in the United Kingdom report that patients arrive with suggestions for treatment based on online search results. However, consumer health wearables are predicted to become the next “Dr Google.” One in six (15%) consumers in the United States currently uses wearable technology, including smartwatches or fitness bands. While 19 million fitness devices are likely to be sold this year, that number is predicted to grow to 110 million in 2018. As the line between consumer health wearables and medical devices begins to blur, it is now possible for a single wearable device to monitor a range of medical risk factors. Potentially, these devices could give patients direct access to personal analytics that can contribute to their health, facilitate preventive care, and aid in the management of ongoing illness. However, how this new wearable technology might best serve medicine remains unclear.

(From the journal abstract)

Piwek, L., Ellis, D. A., Andrews, S., & Joinson, A. (2016). The Rise of Consumer Health Wearables: Promises and Barriers. PLOS Medicine, 13(2), e1001953.

Authors: Lukasz Piwek, David Ellis, Adam Joinson

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