"Since last summer, we’ve been fighting hard against a set of sweeping search warrants issued by a court in New York that demanded we turn over nearly all data from the accounts of 381 people
who use our service, including photos, private messages and other information. This unprecedented request is by far the largest we’ve ever received—by a magnitude of more than ten—and we have argued that
it was unconstitutional from the start."
"Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. […] In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others’ positive experiences constitutes a positive experience for people."
"We study Facebook Connect’s permissions system using crawling, experimentation, and surveys and determine that it works differently than both users and developers expect in several ways. We
show that more permissions can be granted than the developer intended. In particular, permissions that allow a site to post to the user’s profile are granted on an all-or-nothing basis. We evaluate how
the requested permissions are presented to the user and find that, while users generally understand what data sites can read from their profile, they generally do not understand the many different things
the sites can post. In the case of write permissions, we show that user expectations are influenced by the identity of the requesting site which in reality has no impact on what is enforced. We also find
that users generally do not understand the way Facebook Connect permissions interact with Facebook’s privacy settings. Our results suggest that users understand detailed, granular messages better than
those that are broad and vague."
"75. […] It is irrelevant that Mr. Schrems cannot show that his own personal data was accessed in this fashion by the NSA, since what matters is the essential inviolability of the personal
data itself. The essence of that right would be compromised if the data subject had reason to believe that it could be routinely accessed by security authorities on a mass andundifferentiated basis. 76.
Third, the evidence suggests that personal data of data subjects is routinely accessed on a mass and undifferentiated basis by the US security authorities."
"In modern face recognition, the conventional pipeline consists of four stages: detect => align => represent => classify. We revisit both the alignment step and the representation step by
employing explicit 3D face modeling in order to apply a piecewise affine transformation, and derive a face representation from a nine-layer deep neural network. This deep network involves more than 120
million parameters using several locally connected layers without weight sharing, rather than the standard convolutional layers. Thus we trained it on the largest facial dataset to-date, an identity
labeled dataset of four million facial images belonging to more than 4,000 identities, where each identity has an average of over a thousand samples. The learned representations coupling the accurate
model-based alignment with the large facial database generalize remarkably well to faces in unconstrained environments, even with a simple classifier. Our method reaches an accuracy of 97.25% on the
Labeled Faces in the Wild (LFW) dataset, reducing the error of the current state of the art by more than 25%, closely approaching human-level performance."
"Recent reports suggest that an increasing number of organizations are using information from social media platforms such as Facebook.com to screen job applicants. Unfortunately, empirical research concerning the potential implications of this practice is extremely limited. We address the use of social media for selection by examining how recruiter ratings of Facebook profiles fare with respect to two important criteria on which selection procedures are evaluated: criterion-related validity and subgroup differences (which can lead to adverse impact). […] The overall results suggest that organizations should be very cautious about using social media information such as Facebook to assess job applicants."
"We analyzed 700 million words, phrases, and topic instances collected from the Facebook messages of 75,000 volunteers, who also took standard personality tests, and found striking variations in language with personality, gender, and age. In our open-vocabulary technique, the data itself drives a comprehensive exploration of language that distinguishes people, finding connections that are not captured with traditional closed-vocabulary word-category analyses."
"Social networking sites such as Facebook attract millions of users by offering highly interactive social communications. Recently, a counter movement of users has formed, deciding to leave social networks by quitting their accounts (i.e., virtual identity suicide). To investigate whether Facebook quitters (n=310) differ from Facebook users (n=321), we examined privacy concerns, Internet addiction scores, and personality."
"The National Network to End Domestic Violence and Facebook have teamed up to offer tips for survivors of abuse so that you can still use Facebook but maintain safety and control over your information. This guide is aimed at helping survivors of domestic violence, sexual assault and stalking know how to use Facebook in a way that ensures that they stay connected with friends and family, but control their safety and privacy to help prevent misuse by abusers, stalkers, and perpetrators to stalk and harass."
"We have just finished the third wave of our Young People’s Consumer Confidence (YPCC) Index, which is designed to help businesses understand what young people (16-34) think about their current and future economic and employment prospects, in both developed and growth markets. The index which covers 6000 16-34 year olds across six countries revealed some surprising results."
"Recently, we published a blog post that described how to opt out of seeing ads on Facebook targeted to you based on your offline activities. This post explained where these companies get their data, what information they share with Facebook, or what this means for your privacy. So get ready for the nitty-gritty details: who has your information, how they get it, and what they do with it. It’s a lot of information, so we’ve organized it into an FAQ for convenience.”
"This paper discusses the general characteristics of online markets from a competition theory perspective and the implications for competition policy. Three important Internet markets are analyzed in more detail: search engines, online auction platforms, and social networks. Given the high level of market concentration and the development of competition over time, we use our theoretical insights to examine whether leading Internet platforms have non-temporary market power. Based on this analysis we answer the question whether any specific market regulation beyond general competition law rules is warranted in these three online markets."
"Over the past decade, social network sites have experienced dramatic growth in popularity, reaching most demographics and providing new opportunities for interaction and socialization. Through this growth, users have been challenged to manage novel privacy concerns and balance nuanced trade-offs between disclosing and withholding personal information. To date, however, no study has documented how privacy and disclosure evolved on social network sites over an extended period of time. In this manuscript we use profile data from a longitudinal panel of 5,076 Facebook users to understand how their privacy and disclosure behavior changed between 2005|the early days of the network|and 2011."
"We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests."
"When you share content in an online social network, who is listening? Users have scarce information about who actually sees their content, making their audience seem invisible and difficult to estimate. However, understanding this invisible audience can impact both science and design, since perceived audiences influence content production and self-presentation online. In this paper, we combine survey and large-scale log data to examine how well users’ perceptions of their audience match their actual audience on Facebook. We find that social media users consistently underestimate their audience size for their posts, guessing that their audience is just 27% of its true size."