University at Buffalo: What’s the prevailing opinion on social media? Look at the flocks, says UB researcher

University at Buffalo: What’s the prevailing opinion on social media? Look at the flocks, says UB researcher. “…collective views on a topic or issue expressed on social media, distinct from the conclusions determined through survey-based public opinion polling, have never been easy to determine. But the ‘murmuration’ framework developed and tested by Yini Zhang, PhD, an assistant professor of communication in the UB College of Arts and Sciences, and her collaborators addresses challenges like identifying online demographics and factoring for opinion manipulation that are characteristic on these digital battlegrounds of public discourse.”

New York Times: Tone Is Hard to Grasp Online. Can Tone Indicators Help?

New York Times: Tone Is Hard to Grasp Online. Can Tone Indicators Help?. “In a famous study, Albert Mehrabian, a psychology professor at U.C.L.A., found that humans tend to perceive only a fragment of a speaker’s meaning through spoken words. Instead, he observed, most meaning is gleaned from body language and tone of voice. In a text-only environment, how can we ever be certain other people understand what we mean when we post online? Enter tone indicators.”

The Observer: CWU offering students Emotional Intelligence Badges for display on their social media platforms

The Observer: CWU offering students Emotional Intelligence Badges for display on their social media platforms. “[Central Washington University] is offering the first ever Emotional Intelligence Badges for students to display on their social media profiles through its new course, Emotional Intelligence for Professionals (BUS411). The course will lead students through five different modules that break down emotional intelligence, help them understand their own behaviors and work on workplace communication skills.”

JSTOR Daily: How to Meme What You Say

JSTOR Daily: How to Meme What You Say . “In a socially distant world, online life for many people has become normal life. How we express ourselves on the internet has become more important as we lose the social signals of body language and facial expressions. Without handshakes, hugs, and in-person social rituals, such as public gatherings and assemblies, how do we socialize and bond with each other? How can we convey emotionally what our lives have become in this pandemic era without having to explain it all through painstakingly literal language?”

Medium: How Not to Be an Asshole on the Internet

Medium, and I apologize for the swearing: How Not to Be an Asshole on the Internet. “A 2017 study seemed to prove what those of us familiar with online debates have feared for years: People we disagree with seem less human to us when we read their views than when we hear them spoken aloud. Results from a separate 2017 study might help explain why. One: Voices convey emotion, both through the content of what a person says and in how they say it. And two: Intimacy can change everything in these contexts. Seeing someone’s face all the time creates a kind of expertise that allows a person to understand another’s mental state just by looking at them. There’s evidence to suggest that it’s also possible to have this transformation on social media, where we are increasingly conducting our lives.”

Never mind the naysayers: Emoji are a vital part of online communication (Ars Technica)

Ars Technica: Never mind the naysayers: Emoji are a vital part of online communication. “The emergence of emoticons and emoji has been driven by rapid technological changes as the Internet became a dominant force for global mass communication. It has brought along with it the usual handwringing from change-averse elders about how their usage is destroying language. But far from being a unique feature of the Internet era, [Philip] Seargeant argues that human beings have long sought to find these kinds of visual shortcuts to indicate tone.”

Phys .org: Trump’s Twitter communication style shifted over time based on varying communication goals

Phys .org: Trump’s Twitter communication style shifted over time based on varying communication goals. “While many journalists and academics have analysed the topics and sentiment of Trump’s tweets, the range of different rhetorical strategies and discursive styles deployed by Donald Trump is not well studied. The authors of the study downloaded the corpus of tweets sent from the @realDonaldTrump Twitter account from 2009 and 2018 preserved in the Trump Twitter Archive. By analysing patterns of grammatical co-occurence, the authors were able to identify four general style variations of Trump’s tweets: 1) conversational; 2) campaigning; 3) advisory; 4) engaged, and to observe how these stylistic patterns shifted over time.”

The Next Web: This blank Google doc restored our faith in humanity

The Next Web: This blank Google doc restored our faith in humanity. “This week, one of our writers wrote about how he trolled a spammy person by jumping into their bad PR pitch which was unfortunately sent in a public Google doc. We turned their blockchain pitch into a truly Avante Garde and crowd-sourced art project. We were inspired by the results and immediately began to think of other ways we could use crowdsourcing to avoid doing work.”

Dark side of fandom: Study on Blue Jays fan tweets argues sports aren’t always unifying (National Post)

National Post: Dark side of fandom: Study on Blue Jays fan tweets argues sports aren’t always unifying. “After sifting through thousands of tweets about the Toronto Blue Jays, a researcher in Regina is challenging the notion that fandom has a magical ability to unite people. It was a notion peddled constantly during the Jays’ electrifying reign as a playoff contender in 2015 and 2016 – beer commercials, politicians in ball caps, all heralding the official Blue Jays slogan: Come Together. But according to University of Regina PhD candidate Katie Sveinson, Blue Jays fans on Twitter give a starker portrait.”

FreeCodeCamp: We just released 3 years of freeCodeCamp chat history as Open Data — all 5 million messages of it

FreeCodeCamp: We just released 3 years of freeCodeCamp chat history as Open Data — all 5 million messages of it. “This dataset is a record of activity from freeCodeCamp’s most popular chatroom, the general chatroom, which the Gitter team has told me is the most active room on all of Gitter. The dataset contains posts from learners, bots, moderators, and contributors between December 31, 2014 and December 9, 2017.”