Tweets from mobile devices more egocentric

Mobile devices have changed the way we interact with the world. It’s now normal behavior to take selfies or live Tweet an event, but can a mobile device really be an extension of one’s self? A recent study published in the Journal of Communication by researchers at Goldsmiths, Bowdoin College and the University of Maine found that tweets from mobile devices are more likely to employ egocentric language as opposed to non-mobile device Tweets.

The researchers conducted an analysis of tweets to see if presentations of self are more likely to be more egocentric, negative/positive, gendered or communal based on whether users were on a mobile device or using a web based platform.

The researchers found that mobile tweets are not only more egocentric in language than any other group, but that the ratio of egocentric to non-egocentric tweets is consistently greater for mobile tweets than from non-mobile sources. They also did not find that mobile tweets were particularly gendered. Regardless of platform, tweets tended to employ words traditionally associated as masculine.

Previous studies have linked activities performed face-to-face (e.g. eating dinner) to tweets from a particular source. And there has been research that aims to classify tweets as belonging to a particular sentiment by using word lists. This is one of the first studies to take a look at how mobile versus non-mobile plays a part in the language used on social media.

(Do We Tweet Differently From Our Mobile Devices? A Study of Language Differences on Mobile and Web-Based Twitter Platforms, by Dhiraj Murthy, Sawyer Bowman, Alexander J. Gross, and Marisa McGarry; Journal of Communication, doi:10.1111/jcom.12176)

Researchers develop more accurate Twitter analysis tools

“Trending” topics on the social media platform Twitter show the quantity of tweets associated with a specific event. However, trends only show the highest volume keywords and hashtags, and may not give qualitative information about the tweets themselves. Now, using data associated with the Super Bowl and World Series, researchers at the University of Missouri have developed and validated a software program that analyzes event-based tweets and measures the context of tweets rather than just the quantity. The program will help Twitter analysts gain better insight into human behavior associated with trends and events.

“Trends on Twitter are almost always associated with hashtags, which only gives you part of the story,” said Sean Goggins, assistant professor in the School of Information Science and Learning Technologies at MU. “When analyzing tweets that are connected to an action or event, looking for specific words at the beginning of the tweets gives us a better indication of what is occurring, rather than only looking at hashtags.”

Goggins partnered with Ian Graves, a doctoral student in the Computer Science and IT Department at the College of Engineering at MU. Graves developed software that analyzes tweets based on the words found within the tweets. By programming a “bag of words,” or tags they felt would be associated with the Super Bowl and World Series, the software analyzed the words and their placement within the 140 character tweets.

“The software is able to detect more nuanced occurrences within the tweet, like action happening on the baseball field in between batters at the plate or plays in the game,” Graves said. “The program uses a computational approach to seek out not only a spike in hashtags or words, but also what’s really happening on a micro level. By looking for low-volume, localized tweets, we gleaned intelligence that stood apart from the clutter and noise associated with tweets related to the World Series.”

Goggins feels using this method to analyze tweets on a local level can help officials involved with community safety or disaster relief to investigate the causes of major events like the Boston bombing or to help predict future events.

“Most of the things that happen on Twitter are not related to specific events in the world,” Goggins said. “If analysts are just looking at the volume of tweets, they’re not getting the insight they need about what’s truly happening or the whole picture. By focusing on the words within the tweet, we have the potential to find a truer signal inside of a very noisy environment.”

The study, “Sifting signal from noise: a new perspective on the meaning of tweets about the ‘big game,'” was published in the journal, New Media and Strategy.

Twitter is the new TV

New research from scholars at Columbia Business School and the University of Pittsburgh questions the sustainability of Twitter, the social network that has more than 500 million registered users. The research was recently published in the journal Marketing Science.

Columbia Business School Professor Olivier Toubia has a thought-provoking, 140-character-limit comment about the research he co-authored with University of Pittsburgh’s Assistant Professor Andrew T. Stephen.

“Get ready for a TV-like Twitter,” said Toubia.

The research examined the motivations behind why everyday people, with no financial incentive, contribute to Twitter.

The study examined roughly 2500 non-commercial Twitter users. In a field experiment, Toubia and Stephens randomly selected some of those users and, through the use of other synthetic accounts, increased the selected group’s followers. At first, Toubia and Stephen noticed that as the selected group’s followers increased, so did the posting rate. However, when that group reached a level of stature — a moderately large amount of followers — the posting rate declined significantly.

Based on the analyses, Toubia and Stephen predict Twitter posts by everyday people will slow down, yet celebrities and commercial users will continue to post for financial gain.

“Twitter will become less of a communications vehicle and more of a content-delivery vehicle, much like TV. Peer-to-peer contact is likely to evolve to the next great thing, but with 500 million followers, Twitter isn’t just going to disappear. It’s just going to become a new way to follow celebrities, corporations, and the like,” said Toubia.

How to get more followers on Twitter

What do all Twitter users want? Followers – and lots of them. But unless you’re a celebrity, it can be difficult to build your Twitter audience (and even some celebs have trouble). Looking at a half-million tweets over 15 months, a first-of-its-kind study from Georgia Tech has revealed a set of reliable predictors for building a Twitter following.

The research was performed by Eric Gilbert, assistant professor in Georgia Tech’s School of Interactive Computing. Gilbert found that Twitter users can grow their followers by such tactics as:

– Don’t talk about yourself: Informational content attracts followers at a rate 30 times higher than content focused on the tweeter. The study found users talked about themselves in 41 percent of their tweets on average.

– Be happy: Twitter is mainly based on weak social ties (most followers do not know each other offline), which makes it more important to stay away from negative posts such as death, unemployment and poor health.

– Cool it on the hashtags: While hashtags are definitely useful tools for expressing emotional commentary or tying tweets to larger events or issues, they can be abused. Researchers found that the higher a Twitter users’ “hashtag ratio,” the less likely they were to attract new followers.

The study discovered that certain identifiable strategies in message content and interaction with other Twitter users, as well as the structure of one’s Twitter network, have a predictable effect on the number of followers. For example, Twitter “informers” (users who share informational content) consistently attract more followers than “meformers” (users who share information about themselves).

The findings are summarized in the paper A Longitudinal Study of Follow Predictors on Twitter.