“being authentic is very important for social media users. At the same time, users also admitted faking parts of their online image in order to conform to social norms and expectations.”
The above quote is from a ScienceDaily, 14 August 2014 article titled People fake to look real on social media. The story is based on an Aalto University research paper, Social norms and self-presentation on social network sites: Profile work in action.
This is part of a growing body of research on the use (and abuse) of social media. In this case, the researchers focus on two social network sites (SNSs), Facebook and Last.fm, reporting some paradoxical user behaviour. The ScienceDaily article quotes Suvi Uski of Aalto University on this: “Although both of these SNSs differ in the manner in which users are able to share content, we noticed that there was a heavy focus on maintaining a profile that is as natural as possible…We also encountered a widespread disdain by users for what is known as profile tuning, or intentionally sharing content designed to depict the user in a false way.”
On the other hand, co-author of the study Airi Lampinen, notes “While social norms required individuals to be real in their sharing behaviour, presenting oneself in the right way through sharing often necessitated an element of faking.”
The research reports some interesting results for Facebook and in particular for music-sharing platform Last.fm. In both cases, users adjust their behaviour to conform to the “social norm”.
So what implications does this have for Big Data analytics? A previous article discussed the potential dangers in accepting social media data at face value, see The Big Data Debate: “N=All” or “Complete bollocks. Absolute nonsense.” Other recent research looks at this from different perspectives.
“It is a central question whether the interaction and assimilation process in a population leads to a socially beneficial aggregation of information”
This is from a ScienceDaily, May 22, 2014 article, Putting a number on opinion dynamics in a population, based on a Society for Industrial and Applied Mathematics research paper
published in the SIAM Journal of Applied Dynamical Systems. The authors use a mathematical model to study the process of information assimilation in a population resulting from interaction with one’s peers — in-person and via social media– and from the media. The article gives an example of the powerful influence of mainstream media (Fox News) in shaping public opinion in the US.
The authors describe various features of the mathematical model used to provide “a good approximation of the behavior of a large population without relying on detailed social psychological findings.” Those features include “bounded confidence”, “filter bubbles” and “partisan resistance”
Bounded confidence is where “An individual only receives information from individuals and media in his or her confidence bound, i.e., with those opinions close enough to his or her own.”
Filter bubbles are described as “a phenomenon in which websites use algorithms to show users only information that agrees with their past viewpoints, as well as selective exposure, a psychological concept broadly defined as individuals’ tendency to rely on familiar viewpoints.”
Partisan resistance is where “a voter or decision maker ignores the message from an opposing political predisposition.”
The article notes that the authors also take into account the increasing popularity of social media technologies such as blogging and tweeting, which publicly rebroadcast messages with added bias. “In recent times, the direct influence of the media on the public has been augmented by indirect effects of blogging and social networks… Accordingly we model media influence as a background Gaussian signal input centered on the opinion of an expert.” The portion of the population that will be attracted to the input’s center opinion is referred to as the ‘attracted population.’ “We establish that the attracted population is an increasing function of a population’s confidence bound [how close it is to their opinion] and media input’s standard deviation [how much biased rebroadcast of the message occurs] and a decreasing function of the input’s measure (how strongly the message is being broadcast by the media). This result suggests that a higher biased rebroadcast of the media’s message by various blogs, and/or larger public’s confidence bound results in the attraction of a larger population to the advertised message.”
The authors also provide details of how the study was validated by verifying that it follows known properties of opinion evolution, such as clustering of opinions, social learning and manipulation effects caused by misleading input. The study concludes that
“One main future challenge is the study of information assimilation and evolution of public opinions when multiple inputs are considered, for example, when two competing parties debate over their different viewpoints in the mainstream media.”
Some research from Cornell University would suggest that social media has a more pervasive impact than the mathematical models currently recognise.
“People who had positive content experimentally reduced on their Facebook news feed, for one week, used more negative words in their status updates”
Yes, Facebook was involved in the research, unrepentantly manipulating the news feeds of 689,003 users and brushing off the public furore when the report was released, see The Facebook Experiment: What It Means For You. (The Electronic Privacy Information Center (EPIC) filed a complaint with the Federal Trade Commission against Facebook alleging that the social network deceived users and violated a 2012 Consent Order, see Facebook Mood Experiment Draws FTC Complaint.)
The Cornell University research was summarised in a ScienceDaily, 13 June 2014 article Emotional contagion sweeps Facebook, finds new study, based on the Cornell study, Experimental evidence of massive-scale emotional contagion through social networks.
The article gives details of the experiment, noting it is “the first to suggest that emotions expressed via online social networks influence the moods of others…Researchers never saw the content of actual posts, per Facebook’s data use policy; instead, they counted only the occurrence of positive and negative words in more than 3 million posts with a total of 122 million words”
The article also quotes Jeff Hancock, professor of communication at Cornell’s College of Agriculture and Life Sciences and co-director of its Social Media Lab, who noted: “We also observed a withdrawal effect: People who were exposed to fewer emotional posts in their news feed were less expressive overall on the following days…This observation, and the fact that people were more emotionally positive in response to positive emotion updates from their friends, stands in contrast to theories that suggest viewing positive posts by friends on Facebook may somehow affect us negatively.” He also noted that the findings could have implications for public health. “Online messages influence our experience of emotions, which may affect a variety of offline behaviors.”
However, a new study from researchers at the University of Waterloo and Wilfrid Laurier University suggests there may be some truth in the above “theories that suggest viewing positive posts by friends on Facebook may somehow affect us negatively.” A ScienceDaily, 24 June 2014 article, Not everyone wants cheering up, new study suggests, describes a study in the new issue of the Journal of Personality and Social Psychology, titled You can’t always give what you want: The challenge of providing social support to low self-esteem.
The research indicates that people with low self-esteem don’t want positive feedback, they “want their loved ones to see them as they see themselves.” The article quotes Professor Denise Marigold, from Renison University College at Waterloo, and lead author of the study,
“If your attempt to point out the silver lining is met with a sullen reminder of the prevailing dark cloud, you might do best to just acknowledge the dark cloud and sympathize.”
What we are seeing is a growing range of research which takes its data from social media and is still coming to terms with the results. The research has huge potential for social benefit but is also open to misuse. We will return to that subject in a later article.
Aalto University. “People fake to look real on social media.” ScienceDaily. ScienceDaily, 14 August 2014. www.sciencedaily.com/releases/2014/08/140814123925.htm
S. Uski, A. Lampinen. Social norms and self-presentation on social network sites: Profile work in action. New Media & Society, 2014; DOI: 10.1177/1461444814543164
Society for Industrial and Applied Mathematics. “Putting a number on opinion dynamics in a population.” ScienceDaily, 22 May 2014. www.sciencedaily.com/releases/2014/05/140522115802.htm
Anahita Mirtabatabaei, Peng Jia, Francesco Bullo. Eulerian Opinion Dynamics with Bounded Confidence and Exogenous Inputs. SIAM Journal on Applied Dynamical Systems, 2014; 13 (1): 425 DOI: 10.1137/130934040
Cornell University. “Emotional contagion sweeps Facebook, finds new study.” ScienceDaily, 13 June 2014. www.sciencedaily.com/releases/2014/06/140613142533.htm
The original article was written by H. Roger Segelken and Stacey Shackford,
A.D. I. Kramer, J. E. Guillory, J. T. Hancock. Experimental evidence of massive-scale emotional contagion through social networks. Proceedings of the National Academy of Sciences, 2014; DOI: 10.1073/pnas.1320040111
University of Waterloo. “Not everyone wants cheering up, new study suggests.” ScienceDaily, 24 June 2014. www.sciencedaily.com/releases/2014/06/140624142302.htm
Denise C. Marigold, Justin V. Cavallo, John G. Holmes, Joanne V. Wood. You can’t always give what you want: The challenge of providing social support to low self-esteem individuals. Journal of Personality and Social Psychology, 2014; 107 (1): 56 DOI: 10.1037/a0036554