Uncovering key factors that drive the impressions of online emerging technology narratives

Williams, Lowri, Anthi, Eirini and Burnap, Peter ORCID: https://orcid.org/0000-0003-0396-633X 2024. Uncovering key factors that drive the impressions of online emerging technology narratives. Information 15 (11) , 706. 10.3390/info15110706

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Abstract

Social media platforms play a significant role in facilitating business decision making, especially in the context of emerging technologies. Such platforms offer a rich source of data from a global audience, which can provide organisations with insights into market trends, consumer behaviour, and attitudes towards specific technologies, as well as monitoring competitor activity. In the context of social media, such insights are conceptualised as immediate and real-time behavioural responses measured by likes, comments, and shares. To monitor such metrics, social media platforms have introduced tools that allow users to analyse and track the performance of their posts and understand their audience. However, the existing tools often overlook the impact of contextual features such as sentiment, URL inclusion, and specific word use. This paper presents a data-driven framework to identify and quantify the influence of such features on the visibility and impact of technology-related tweets. The quantitative analysis from statistical modelling reveals that certain content-based features, like the number of words and pronouns used, positively correlate with the impressions of tweets, with increases of up to 2.8%. Conversely, features such as the excessive use of hashtags, verbs, and complex sentences were found to decrease impressions significantly, with a notable reduction of 8.6% associated with tweets containing numerous trailing characters. Moreover, the study shows that tweets expressing negative sentiments tend to be more impressionable, likely due to a negativity bias that elicits stronger emotional responses and drives higher engagement and virality. Additionally, the sentiment associated with specific technologies also played a crucial role; positive sentiments linked to beneficial technologies like data science or machine learning significantly boosted impressions, while similar sentiments towards negatively viewed technologies like cyber threats reduced them. The inclusion of URLs in tweets also had a mixed impact on impressions—enhancing engagement for general technology topics, but reducing it for sensitive subjects due to potential concerns over link safety. These findings underscore the importance of a strategic approach to social media content creation, emphasising the need for businesses to align their communication strategies, such as responding to shifts in user behaviours, new demands, and emerging uncertainties, with dynamic user engagement patterns.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	MDPI
Funders:	ESRC
Date of First Compliant Deposit:	4 November 2024
Date of Acceptance:	4 November 2024
Last Modified:	05 Nov 2024 14:33
URI:	https://orca.cardiff.ac.uk/id/eprint/173631

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