If you want to influence public opinion on Twitter, the trick is to get your message out early. Once your message is stabilized on the social medium, it’s too difficult for your competitors to overcome your lead according to research released in 2014.
The researchers’ conclusions show how marketers and politicians can achieve greater awareness to influence public opinion.
So how do the more than 240 million tweeters, who tweet some 500 messages each day, shape public opinion?
Beijing Jiaotong University Lecturer Fei Xiong and Professor Yun Liu say they’ve learned how it works. They contend that when a message is quickly published, it takes hold and begins to become dominant.
“By focusing on a network application, candidates or companies can analyze the characteristics and behavior patterns of their supporters and protesters to explore whether the measures they take can influence public opinion and which opinion may succeed,” said Mr. Xiong.
The researchers say opinions are thrust to the forefront by multiple tweets and retweets forming dominant pressure.
In a press release, the study shows when dominant opinions emerge, however, they tend not to achieve complete consensus.
Researcher Xiong said Twitter users who hold minority views are faced with overwhelming opposition aren’t likely to change their opinions.
“Once public opinion stabilizes, it’s difficult to change,” he added.
The study also revealed that Twitter users overall are more likely to work to change the opinions of others than to admit to changes of their own.
Caption: The public opinion for each topic fluctuates in the early stage, and then the dynamics is extremely slowed down after a short time. Ultimately, the public opinion evolves into an ordered state and one opinion predominates absolutely, but a state of complete consensus is difficult to reach. At first, one opinion takes a slight advantage, but this advantage gradually grows toward the initial majority opinion in the evolution process.
The researchers investigated how opinions evolve on Twitter by gathering about 6 million 140-character-or-less messages that were tweeted over a six-month period in the first half of 2011.
They ran these messages through computer algorithms that sorted them by topic (“iPhone 4” or “blackberry,” for instance), and they analyzed the underlying sentiments of the authors as they evolved over time.
The study was published in the journal Chaos, produced by AIP Publishing.
The article, “Opinion Formation on Social Media: An Empirical Approach” by Fei Xiong and Yun Liu in Chaos: An Interdisciplinary Journal of Nonlinear Science (DOI: 10.1063/1.4866011) can be viewed at http://tinyurl.com/ptbq7m4.
Chaos: An Interdisciplinary Journal of Nonlinear Science is devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines (see http://chaos.aip.org/).
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“Twitter is my bar. I sit at the counter and listen to the conversations, starting others, feeling the atmosphere.”