According to US researchers, after Elon Musk (CEO of Twitter) took over social media. Changes in Twitter algorithms show that the tweets used by users amplify anger and animosity.
Recent discoveries from researchers at Cornell University and UC Berkeley reveal data on this matter. Changes in Twitter’s algorithms and their effects on user behavior.
This study, done recently, concentrates on the tweets featured on users’ personalized timelines and the sequential timeline. The research was done with data extracted from 806 users in February. There was a significant rise in tweets that amplified anger and animosity.
According to the research, Twitter’s algorithm now gives more priority to “emotional content,” evoking users to react more strongly. Even though the original cause of the tweets wasn’t necessarily to provoke such a response. The researchers discovered that the algorithm enhances tweets expressing anger. This results in increased emotional responses, including high levels of anger, among users.
The researchers noted that the display of political tweets used to change user conduct, which enhanced othering behavior. Which includes unfavorable beliefs about a group of people having contrary beliefs.
“The political tweets shown by the algorithm exhibit greater partisanship and out-group animosity. Moreover, the algorithm slightly increases the ratio of out-group to in-group content (rather than reinforcing filter bubbles or echo chambers),” the researchers wrote.
The use of these algorithm base tweets results in users seeing their political in-group more positively and the political out-group more negatively. This will contribute to greater affective factionalism.
As a result of more users liking the content and following people with various types of opinions. They were likely to observe emotional content on the platform.
Cornell and UC Berkeley researchers have experimented with no internal access, only using participants who allowed them to use their tweets after signing up on the online crowd-working platform CloudResearch Connect.
“As social media continues to have a significant influence on public opinion, understanding the impact of the machine-learning algorithms that filter and curate content is crucial,” they said.
“ We believe that the short-term effects from our study on the amplification of content (eg emotional content, partisan content, and out-group animosity) may be indicative of larger long-term effects.”
Can polarising content be dangerous to society?
Marvin Winkelmann, MD of talent management and content creation marketing agency AFK believes that there is no hate or anger content on Twitter today.
“Engaging in discussions is part of human nature, and there is evidence to support that contentious subjects generate significantly more interaction compared to topics where there is a consensus,” he told The Standard.
“As the audience size increases, a greater number of contentious opinions need to be expressed.For example, accounts with the most active followers highly benefit from this and this is why Elon Musk has very high engagement rates within his follower count.”
He mentioned that due to the availability of controversial topics, consequently, there seems to be a proliferation of negative content.
“If we compare two topics like, ‘What is your favorite pizza?’ and ’Does pineapple belong on pizza?’, every single time the pineapple topic will rank higher in the algorithm and have much higher engagement due to the controversy and strongly opposed opinions,” added Mr. Winkelmann.
Recent Twitter variations to algorithms simply enhance this. As a consequence of the highly controversial topics, people frequently perceive it as negative, notwithstanding its positive nature. This is primarily attributable to the abundance of comments and disagreements surrounding the discussions.
