In social media marketing, where the transmission of messages is incessant, researchers from the UK have investigated the concept of different kinds of message noise, which act as barriers to clear communication by distorting the social media messages.
Writing in the International Journal of Internet Marketing and Advertising, Kimberley Hardcastle, Prabash Edirisingha, and Paul Cook of Northumbria University, Newcastle, explain how they carried out a 21-month study to analyse data from the well-known social media sites Instagram and Twitter, now known as X, based on an analysis of hashtags. Hashtags are keywords used with a hash, #, to help users define the content they post and for other users to find content of interest in a particular area.
The team identified three main types of message noise: technical, material, and architectural. Technical noise stems from software and hardware limitations, material noise arises from intentional, and perhaps unintentional, design features of platforms and devices, and architectural noise emerges from network interactions.
The researchers identified five key interception points where message meaning can become distorted on social media. This distortion affects how consumers interpret those incessant messages on their smart devices. In addition, the research shows that the user’s choice of communication platform and device can greatly influence how well a message is transmitted and received and subsequently interpreted. Moreover, specific functionality of the platform being used also affects message retrieval and interpretation.
In practical terms, the findings might help guide digital marketing practitioners. By understanding the nature of material noise marketers can find better ways to help their would-be customers navigate technological barriers. For instance, guiding consumers to access messages across different platforms or encouraging them to develop skills to navigate material noise effectively.
The work also shows that there has been limitations in our understanding of noise in social media communication so far. The team urges fellow researchers to look more deeply into this area to improve still further our understanding and how they affect human and “non-human” choices made in response to the interpretation of a given message.
Hardcastle, K., Edirisingha, P. and Cook, P. (2024) ‘Identifying sources of noise within the networked interplay of marketing messages in social media communication’, Int. J. Internet Marketing and Advertising, Vol. 20, No. 2, pp.164–187.