Online social media influence the flow of news and other information, potentially altering collective social action while generating a large volume of data useful to researchers. Mapping these networks may make it possible to predict the course of social and political movements, technology adoption, and economic behavior. Here we map the network formed by Twitter users sharing British Broadcasting Corporation (BBC) articles. The global audience of the BBC is primarily organized by language with the largest linguistic groups receiving news in English, Spanish, Russian and Arabic. Members of the network primarily “follow” members sharing articles in the same language, and these audiences are primarily located in geographical regions where the languages are native. The one exception to this rule is a cluster interested in Middle East news which includes both Arabic and English speakers. We further analyze English-speaking users, which differentiate themselves into four clusters: one interested in sports, two interested in United Kingdom (UK) news—with word usage suggesting this reflects political polarization into Conservative and Labour party leanings—and a fourth group that is the English speaking part of the group interested in Middle East news. Unlike the previously studied New York Times news sharing network the largest scale structure of the BBC network does not include a densely-connected group of globally interested and globally distributed users. The political polarization is similar to what was found for liberal and conservative groups in the New York Times study. The observation of a primary organization of the BBC audience around languages is consistent with the BBC’s unique role in history as an alternative source of local news in regions outside the UK where high quality uncensored news was not available.
CAMBRIDGE (Aug 20, 2013) — Where do people get their news, and how does information spread through social networks? Researchers at the New England Complex Systems Institute (NECSI) analyzed how BBC articles are shared through Twitter, and discovered how the BBC successfully reaches multiple audiences. Mapping social networks, especially around the dissemination of news, makes it possible to forecast—with a growing degree of accuracy—social and political movements, technology adoption, and economic behavior.
The report, “An Exploration of Social Identity: The Structure of the BBC News-Sharing Community on Twitter,” by Julius Adebayo, Tiziana Musso, Kawandeep Virdee, Casey Friedman, and Yaneer Bar-Yam, looked at almost 500,000 tweets sharing BBC links over the course of six days, and created a map of the network of who is following whom.
The BBC is unique in that it provides local news in multiple languages around the world. This is apparent in the study, as there are substantial separate audiences for Russian, Spanish, Arabic, and English coverage, with connections within each language group but very few connections between them. The authors attribute this linguistically and geographically widespread influence to the BBC’s historical role as the provider of trustworthy news in countries with histories of press restrictions, including Chile, Egypt, Mexico, Pakistan, Russia, and Venezuela.
Twitter users who share BBC articles in English can further be divided into four subgroups. One is primarily focused on sports; two other clusters are mostly interested in UK news—one apparently associated with the Conservative party (with the frequent keywords being “business,” “marketing,” and “financial”) and one with the Labour party (“politics,” “student," “science,” and “labour”), reflecting the political polarization of the British electorate. The fourth group is primarily focused on the Middle East. While the first three are mostly composed of users from the UK, the last group is closely linked to many Arabic speakers from the Middle East. Unlike previous research conducted by the same authors using stories from The New York Times, the analysis did not show any overarching cosmopolitan group.
“We know that social media is playing a role in revolutionary events in the world and therefore knowing how people interact with each other can help us understand or even anticipate social events” said Bar-Yam. “Science is giving us the opportunity to map these global social interactions.”