January 10, 2013
No Single Best Way To Spread News On Twitter: Study
redOrbit Staff & Wire Reports - Your Universe Online
A new study finds that news spreads throughout Twitter in a variety of ways, and that there is no single, universally applicable strategy to maximize the effectiveness of dispersing news across the microblogging site.
But news agencies can still learn a lot by examining how their news diffuses once it is posted on Twitter, researchers said.
Over a six month time period, University of Arizona professor Sudha Ram studied a dozen major news organizations that use Twitter as one tool for sharing their content.
The news agencies -- The New York Times, Washington Post, BBC, NPR, Reuters, Guardian, Forbes, Financial Times, Mashable, Arstechnica, Wired and Bloomberg — were all focused on global news, technology news or financial news, and regularly shared stories on Twitter.
Ram tracked what happened to a news article after it was tweeted by a news organization, such as how many people re-tweeted or re-posted the story, and how many times the story was subsequently re-tweeted.
She then calculated the volume and extent of a news story´s spread, as well as its overall lifespan.
"The goal for a news agency is to have a lot of people reading and following your articles," said Ram, McClelland Professor of Management Information Systems in the UA's Eller College of Management.
"What we've done is use network analysis, which is quite different from just looking at the total number of tweets or total number of re-tweets. You're starting to see, over time, how information is spreading."
Ram and Devi Bhattacharya, a UA MIS doctoral student, rendered the data they collected from each organization visually as images, which revealed how the news is diffused.
The network visualizations resemble fireworks, with dots representing individual twitter users and cascade streams from those dots depicting re-tweets. The images show different diffusion patterns for the different agencies, which can provide clues to those organizations about how their news is spreading and what they might want to focus on to be successful, Ram said.
"This gives them good feedback, and it's kind of a performance report for them," Bhattacharya said.
"It gives them an idea about the reading habits of people online and how they like to consume news."
Of the organizations analyzed, BBC had the maximum reach in terms of affected users and re-tweet levels, Ram said.
BBC articles also had the highest chance of survival on Twitter, with 0.1 percent of articles surviving, through continual re-tweets, for three or more days. The BBC's performance was likely attributable to the fact that the main "bbcnews" Twitter account also is supported by two other agency accounts — "bbcbreaking" and "bbcworld," Ram said.
The New York Times and Mashable had the second highest reach, while stories from Forbes, Wired and Bloomberg had the shortest Twitter lifespans.
Overall, Ram said the data showed that articles on Twitter dissipate fairly quickly, with re-tweeting typically ending between 10 and 72 hours after an article is originally published.
The Twitter study sets the stage for further research into how news is disseminated throughout various social media platforms.
Ram plans to present a follow-up paper at the Workshop on Information Technologies and Systems in Florida later this year on the importance of Twitter-follower engagement for news organizations, as opposed to volume of followers.
"The term 'social media' refers to a lot of things. The first thing people think about is Facebook and then Twitter, but it's so much more than that," Ram said.
"It's really all the various forums — the blogs, photo sharing sites, video sharing sites, microblogging, social bookmarking like Digg, Delicious and Reddit and so on."
Ram says she hopes to do more extensive research on news sharing, and develop partnerships with news agencies to help them answer specific questions about their social media practices and performance.
"The idea is really to see if we can make some predictions," Ram said.
"What are some attributes of these networks that will help us make predictions? Is it number of followers? Is it engagement of followers? Is it what time you tweet? Is it who else is tweeting at the same time? Which are the more useful attributes that will help us predict, and therefore will help us give organizations suggestions on how to be more effective in spreading their news? Because ultimately their goal is more people reading their articles and talking about them."
Image 2 (below): The Twitter Activity Network for The New York Times shows a high number of users participating in long chains of tweeting and retweeting.