Public opinion on social media can seem to have a mind of its own sometimes, but research from the University of Buffalo strives to better understand the apparent murmurations online.

The researchers develop a framework that they believe helps to address issues like the online demographics of people online and the way opinions can be manipulated.

Who follows whom

The murmuration effect is commonly seen in flocks of birds, and is based on the concept of “who-follows-whom” relationships. Online, this manifests itself when people attract like-minded others to follow them and form “flocks”. The authors argue that when opinions both form and shift, they act as a form of a fluid murmuration of birds.

The framework was formed after analyzing over 193,000 Twitter accounts, who between them were following around 1.3 million other accounts. The authors believe that it can help to predict both opinions and the intensity of those opinions. The findings support the tendency of networks to form echo chambers.

“By identifying different flocks and examining the intensity, temporal pattern and content of their expression, we can gain deeper insights far beyond where liberals and conservatives stand on a certain issue,” the researchers say. “These flocks are segments of the population, defined not by demographic variables of questionable salience, like white women aged 18–29, but by their online connections and response to events.”

“As such, we can observe opinion variations within an ideological camp and opinions of people that might not be typically assumed to have an opinion on certain issues. We see the flocks as naturally occurring, responding to things as they happen, in ways that take a conversational element into consideration.”

This murmuration provides us with valuable insights that can augment those derived from surveys and more traditional methods. The authors also believe that the approach goes away from the process of mining social media for specific tweets and takes better advantage of the dynamic aspect of social media. This is important as when text is removed from its context it can be hard to reliably determine how the conversation emerged, when it started, and how it changed over time.

“Murmuration can allow for research that makes better use of social media data to study public opinion as a form of social interaction and reveal underlying social dynamics,” the authors conclude.