The impact of social noise on social media and the original intended message: BLM as a case study

Abstract

Social media has become a platform for information diffusion, voicing concerns of existing inequalities and raising public awareness of various social and societal issues. Despite the social good, social media has become a fertile ground for spreading misinformation, hate speech and conspiracy theories. The death of George Floyd in May 2020 triggered a series of protests worldwide in support of the Black Lives Matter (BLM) movement and triggered a debate about equity, inclusion and social justice. The purpose of this study is to examine the impact of misinformation and social noise on the original intended message of BLM using data from the Twitter hashtag ‘BLM’. Results from topic modelling have shown the strong presence of misinformation and social noise. Such information was most probably intended to influence, mislead and dilute the original intended message. However, despite the effort to distort the original message of BLM, results from sentiment analysis show that users’ opinions of the BLM movement remained positive.

Identifying sources of noise within the networked interplay of marketing messages in social media communication.

“…Our research shows that the disparate interplays between actors in social media network interfaces create message noise and distortion. In particular, our findings demonstrate that the interdependent nature of message noise elements (Pampapura et al, 2022) and the variegated potential of converging network actants contribute to multiple levels of marketing message mutations. Our framework (Figure 2), demonstrates five key interception points that have the propensity to distort the intended message meaning, hampering consumers' opportunity and ability to interpret those messages.…”

“…Referred to as "noise" within communication and transmission literature (Shannon, 1949), the distortion of social media messages relates to particular consequences that result from complex network interactions that typify message exchange (Fox, & Lind, 2020). However, little attention is devoted in the extant literature towards understanding the nature of message "noise" and the role of actor interplays in the process of social media message dissemination (Pampapura, et al, 2022). For example, viral message mutations are defined as changes to the functional and structural components of messages during one or more stages of the replication process whereby the message passes from one person to the next, primarily through electronic means (Fox, & Lind, 2020;Kaplan & Haenlein 2011).…”

The Impact of Social Media on COVID-19 Vaccine Hesitancy and Acceptance: Data Analytic Approach

“…Women have shown higher skepticism about the productivity and benefit of the COVID-19 vaccine than men. Studies also shown that extended exposure to social media and increased participation in social noise can also lead to the spread of COVID-19 misinformation and conspiracy theories (Jolley & Douglas 2017;Jolley & Douglas, 2014;Alasid et al, 2020;Pampapura Madali et al, 2022). Efforts to combat misinformation and conspiracy theories will require a better understanding other factors impacting vaccine hesitancy…”