Facebook feelings are contagious: Study examines how emotions spread online
You can’t catch a cold from a friend online. But can you catch a mood? It would seem so, according to new research from the University of California, San Diego. Published in PLOS ONE, the study analyzes over a billion anonymized status updates among more than 100 million users of Facebook in the United States. Positive posts beget positive posts, the study finds, and negative posts beget negative ones, with the positive posts being more influential, or more contagious. “Our study suggests that people are not just choosing other people like themselves to associate with but actually causing their friends’ emotional expressions to change,” said lead author James Fowler, professor of political science in the Division of Social Sciences and of medical genetics in the School of Medicine at UC San Diego. There is abundant scientific literature on how emotion can spread among people – through direct contact, in person – not only among friends but also among strangers or near-strangers.
Tool – An advanced concept of information analysis
NodeXL: Network Overview, Discovery and Exploration for Excel - Home
A Dr. Seuss-Inspired Guide to Twitter
Dr. Seuss, the writer and illustrator behind children’s classics The Cat in the Hat, How the Grinch Stole Christmas! and The Lorax, would have turned 110 on March 2nd. Can you think of a Seuss-inspired social media rhyme? A Seuss Twitter: Although it might feel, like a mountain to climb Twitter really is simple, if you put in the time. Doug Bowman (@stop) February 28, 2014 A Seuss Twitter: “Horton will Trumpet, The Grinch will Howl. It’s a Seussian day for all friends of the rhymer, at one-hundred and ten he’d be an old-timer. @hootsuite Do you like Tweets that are spam? The best flow is on the go! And if no one follows back, don’t be offended In due time they will see that you’re so splendid. Original artwork by @designowls Here’s a slideshare version of the illustration for easy sharing. And the poem, in text: One Tweet, Two Tweets, Old Tweets, New Tweets, Short Tweets, Long Tweets, Right Tweets, Wrong Tweets; Tweets about content, content about Tweets.
Measuring Large-Scale Social Networks with High Resolution
This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. Figures Citation: Stopczynski A, Sekara V, Sapiezynski P, Cuttone A, Madsen MM, et al. (2014) Measuring Large-Scale Social Networks with High Resolution. Introduction Related Work
Cartelera: CFHE12: Analítica de la Twitteresfera.
Entendiendo la foto del evento Los mensajes publicados en Twitter, sobre todo asociados a eventos como el MOOC "Current/Future Status of Higher Education 2012 (#CFHE12)" reflejan su dinámica mediante la Twitteresfera o conjunto de tuits que se pueden agrupar mediante una etiqueta o "hashtag" para su análisis. Sin embargo, las relaciones entre los autores, tales como publicar, seguir, responder o retuitear un mensaje, no son claras a simple vista, en especial si esa nube de mensajes es densa. El Análisis de Redes Sociales (ARS o SNA por sus siglas en inglés) brinda una gama cada vez más amplia de herramientas para develar la estructura de relaciones que emergen a partir de las interacciones mencionadas. Esta es "la foto completa", misma que a simple vista no aporta mayor información. - Análisis de interacciones individuales Para el momento del análisis, viernes 02 de noviembre, un total de 133 participantes mostraron 932 interacciones representadas por las aristas del grafo. . http:/:
Social Network Analysis Reveals Full Scale of Kremlin’s Twitter Bot Campaign
Profile pictures from a large network of pro-Kremlin Twitter accounts. Image by Lawrence Alexander. With the aid of open-source tools, Internet researcher Lawrence Alexander gathered and visualised data on nearly 20,500 pro-Kremlin Twitter accounts, revealing the massive scale of information manipulation attempts on the RuNet. In what is the first part of a two-part analysis, he explains how he did it and what he found. RuNet Echo has previously written about the efforts of the Russian “Troll Army” to inject the social networks and online media websites with pro-Kremlin rhetoric. Twitter is no exception, and multiple users have observed Twitter accounts tweeting similar statements during and around key breaking news and events. But the evidence in this two-part analysis points to their role in an extensive program of disinformation. Using the open-source NodeXL tool, I collected and imported a complete list of accounts tweeting that exact phrase into a spreadsheet.
7 Ways to Make your Tweet Go Viral
Tweets going viral are not by accident and it’s obvious tweets are the lifeline of Twitter. Any business planning to use Twitter for business purpose needs to have an effective tweeting strategy in place. There is no doubt that Twitter has redefined how businesses spread information online. Viral tweets also help bring significant traffic to your business website, which in turn can boost your subscriber numbers. Catchy, Interesting & Informational Content I come across several clients who confess that they find the 140-character limit on Twitter to be a huge dampener for their business. What are the tips your business follows to ensure that your tweets have a viral effect? Share this to share your insight with others. Want more stuff like this? Douglas Idugboe Douglas Idugboe, Digital and New Media Marketing Strategist. Latest posts by Douglas Idugboe (see all)
The Emerging Science of Superspreaders (And How to Tell If You're One Of Them)
Who are the most influential spreaders of information on a network? That’s a question that marketers, bloggers, news services and even governments would like answered. Not least because the answer could provide ways to promote products quickly, to boost the popularity of political parties above their rivals and to seed the rapid spread of news and opinions. So it’s not surprising that network theorists have spent some time thinking about how best to identify these people and to check how the information they receive might spread around a network. But there’s a problem. But there is growing evidence that information does not spread through real networks in the same way as it does through these idealised ones. So the question of how to find the superspreaders remains open. In the past, network scientists have developed a number of mathematical tests to measure the influence that individuals have on the spread of information through a network.
