Popularity of Social Media on the Rise
Over the past decade, social media has become so ubiquitous that, as of 2016, 69% of the public uses some type of social media (Pew Research Center, 2017). Pew Research Center, a nonpartisan American "fact tank", has documented the wide variety of ways in which Americans use social media to seek out information and interact with others. Unfortunately, a majority of Americans now say they get news via social media, in which half of the public has turned to these sites to learn about the 2016 presidential election. Whether users are using social media in the context of work (whether to take a mental break on the job or to seek out employment), users are in an ongoing effort to navigate the complex privacy issues that these sites bring to the forefront.
Facebook (FB) continues to remain the most popular social media platform, with its users visiting the site more regularly than users of other social media sites. Roughly three-quarters (76%) of FB users report that they visit the site daily (55% visit several times a day, and 22% visit about once per day). Instagram and Twitter occupy the middle tier of social media sites in terms of the share of users who log in daily. Roughly half (51%) of Instagram users access the platform on a daily basis, with 35% saying they do so several times a day. And 42% of Twitter users indicate that they are daily visitors, with 23% saying they visit more than once a day. A slightly larger share of Americans use Pinterest and LinkedIn than use Twitter, but users of these sites are less likely than Twitter users to check in every day: 25% of Pinterest users and 18% of LinkedIn users are daily visitors. Social media users continue to use a relatively diverse array of platforms. More than half of online adults (56%) use more than one of the five social media platforms. As the most-used social media site, FB continues to be the starting platform for most social media users (Greenwood, Perrin & Duggan, 2016). |
Did You Know?
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Corporate-Controlled Platforms
After acknowledging that the majority of internet users use social media, specifically FB, becoming aware of how many of these platforms merge and acquire may shed light on the intentions of these companies; since companies, like FB, are now completely engrained in our society and our everyday lives. For example, Instagram has been acquired by FB since 2012, and YouTube acquired by Google in 2006, Vine acquired by Twitter since 2012, LinkedIn acquired by Microsoft in 2016, among others. It is important to become informed about these select groups of corporations that control the flow of information and media to a vast majority of the global population.
Able to Detect Emotions
A patent filed in 2014 describes plans to detect users emotions and deliver specific content, based on those emotions, through computing devices such as laptops, mobile phones and tablets that have a digital camera. The patent works by an application programming interface (API) component that is able to utilize the imaging component on the device to detect emotion characteristics and store an association between the presented type of emotion and the detected emotion characteristics in the storage component. Once detected and identified, an emotion type may be stored, either temporarily for a defined period of time, or permanently in a user profile.
"A need exists for delivering content a user that may be of current interest to them...[which] may be determined based upon their current emotional state." The patent goes on, "current content delivery systems typically do not utilize passive imaging information. Thus, a need exists for a content delivery solution that takes advantage of available passive imaging data to provide content to a user with improved relevancy."
"Content delivery may be performed by an application stored on a device, such as a social networking application, or using a browser application, which may access content from the internet. Content may include, but is not limited to, social networking posts, photos, videos, audio, games, advertisements, or applications made available online or through an application store[d] on a device."
"Devices without limitation include a mobile device, a personal digital assistant, a mobile computing device, a smart phone, a cellular telephone, a handset, a one-way pager, a two-way pager, a messaging device, a computer, a personal computer, a desktop computer, a laptop computer, a notebook computer, a handheld computer, a tablet computer, or a wearable computer, such as a smart watch."
"Applications may include, but are not limited to, native mobile applications, web applications, desktop applications, or any combination thereof. Examples of native mobile applications may include social networking applications, newsreader applications, photography applications, video applications, media applications, search applications, games, e-reading applications, or the like."
"Devices may further include sensors, which may include accelerometer, temperature, gravity, light, accleration, magnetic field, orientation, pressure, rotational vector, or other sensors capable of sensing characteristics of a device and its environment."
Examples of operating systems that may be used by device include Apple iOS, Apple OS X, Google Android, Google Chrome OS, Microsoft Windows, or Microsoft Windows Phone.
An emotion characteristic may indicate feelings, moods, or expressions that can be categorized into types of emotions. Types of emotions may include emotions or expressions such as a smile, joy, humor, amazement, excitement, surprise, a frown, sadness, disappointment, confusion, jealousy, indifference, boredom, anger, depression, or pain. The patent also describes how it is able to detect whether a user is looking at a device or away from a device. Over a period of time, emotion detection may determine a user's interest in displayed content using a combination of detected emotion types. In this manner, a type of emotion may be associated with viewed content and content displayed to the user may be customized based upon emotion type (Techniques for emotion detection..., 2017).
Whether this technology will be implemented or not, in the meantime, it may be best to put tape over your devices' cameras, unless you would prefer to participate in, and thus consent to, becoming exploited and the end of your right to privacy.
"A need exists for delivering content a user that may be of current interest to them...[which] may be determined based upon their current emotional state." The patent goes on, "current content delivery systems typically do not utilize passive imaging information. Thus, a need exists for a content delivery solution that takes advantage of available passive imaging data to provide content to a user with improved relevancy."
"Content delivery may be performed by an application stored on a device, such as a social networking application, or using a browser application, which may access content from the internet. Content may include, but is not limited to, social networking posts, photos, videos, audio, games, advertisements, or applications made available online or through an application store[d] on a device."
"Devices without limitation include a mobile device, a personal digital assistant, a mobile computing device, a smart phone, a cellular telephone, a handset, a one-way pager, a two-way pager, a messaging device, a computer, a personal computer, a desktop computer, a laptop computer, a notebook computer, a handheld computer, a tablet computer, or a wearable computer, such as a smart watch."
"Applications may include, but are not limited to, native mobile applications, web applications, desktop applications, or any combination thereof. Examples of native mobile applications may include social networking applications, newsreader applications, photography applications, video applications, media applications, search applications, games, e-reading applications, or the like."
"Devices may further include sensors, which may include accelerometer, temperature, gravity, light, accleration, magnetic field, orientation, pressure, rotational vector, or other sensors capable of sensing characteristics of a device and its environment."
Examples of operating systems that may be used by device include Apple iOS, Apple OS X, Google Android, Google Chrome OS, Microsoft Windows, or Microsoft Windows Phone.
An emotion characteristic may indicate feelings, moods, or expressions that can be categorized into types of emotions. Types of emotions may include emotions or expressions such as a smile, joy, humor, amazement, excitement, surprise, a frown, sadness, disappointment, confusion, jealousy, indifference, boredom, anger, depression, or pain. The patent also describes how it is able to detect whether a user is looking at a device or away from a device. Over a period of time, emotion detection may determine a user's interest in displayed content using a combination of detected emotion types. In this manner, a type of emotion may be associated with viewed content and content displayed to the user may be customized based upon emotion type (Techniques for emotion detection..., 2017).
Whether this technology will be implemented or not, in the meantime, it may be best to put tape over your devices' cameras, unless you would prefer to participate in, and thus consent to, becoming exploited and the end of your right to privacy.
Able to Manipulate Emotions
In a massive experiment, conducted on nearly 700,000 users in 2014, FB manipulated the extent to which people were exposed to emotional expressions in their News Feed, to test whether exposure to emotions led people to change their own posting behaviors; in particular whether exposure to emotional content led people to post content that was consistent with the exposure. If you are not familiar with FB, the News Feed is the primary manner by which FB users see content that friends share. Which content is shown or omitted in the News Feed is determined via a ranking algorithm that Facebook continually modifies and tests in the interest of showing viewers the content that FB finds most relevant and engaging. The experiment was conducted on the premise that emotional states can be transferred to others via emotional contagion, leading them to experience the same emotions as those around them. That is, people have the ability to transfer both positive and negative moods and emotions to others. Researchers have determined that, based on data from a large, real-world social network collected over a 20-y period, suggests that depression and happiness are able to be transferred through social networks as well (Kramer, Guillory, & Hancock, 2014). For example, Turkle (2011), suggests that when individuals participate in online social networks and are exposed to the happiness of others, the resulting reaction may actually be depressing to the individual, producing an “alone together” social comparison effect. Sure enough, the researchers observed that 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 suggest that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale emotional contagion via social networks. In addition, these results suggests that in-person interaction and non-verbal cues are not strictly necessary for emotional contagion.
According to The Australian, a leaked memo states that Fb can establish when users are feeling “stressed,” “defeated,” “overwhelmed,” “anxious,” “nervous,” “stupid,” “silly,” “useless,” and a “failure,”, by monitoring users’ posts, media uploads, interactions on the platform, and their overall internet activity.
According to The Australian, a leaked memo states that Fb can establish when users are feeling “stressed,” “defeated,” “overwhelmed,” “anxious,” “nervous,” “stupid,” “silly,” “useless,” and a “failure,”, by monitoring users’ posts, media uploads, interactions on the platform, and their overall internet activity.
Funding and Spreading of Fake-News
In the war on information, Facebook's adoption of a "third-party fact checking" organization dedicated to retain and to flag, and thus eliminate "fake news", should come at no surprise. In 2016, Facebook posted the following press release to their website detailing their plans to use a "third-party fact checking organization," known as The Poynter Institute, to flag "fake news." The role of the "fact checkers" will be to review news stories and flag anything they deem to be "fake" so that it can be deprioritized on Facebook's news feed.
Of course, that raises any number of questions including what will be deemed to be "fake news" (e.g. will dissenting opinions be deemed "fake") and who exactly gets to oversee such a powerful position that basically has been given carte blanche to censor media outlets of their choosing? Surely such an organization would have to be an extremely transparent, publicly funded, bi-partisan group, right?
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Well, not so much apparently. A quick review of Poynter's website reveals that the organization is funded by the who's who of leftist billionaires including George Soros' Open Society Foundations, the Bill & Melinda Gates Foundation, Google, and Ebay founder Pierre Omidyar's Omidyar Network. Well that seem fairly bipartisan, right?
But don't worry, Poynter would like to assure you that they're committed to "nonpartisan and transparent fact-checking." |
The Evolution of Privacy Policies
Marketing Through Social Media: Psychographics
Psychographics: the study of personality, values, opinions, attitudes, interests, and lifestyles.
You Have Agreed to the Following
By participating in these platforms, you agree to their terms and conditions, and thus consent of the company's behaviors. Platforms that exploit their users are, generally, free for a reason.
How Your Data Can Harm You
Everyone is a Suspect
Data Can Be Used to Prevent Protest
Your Phone Company Shares Everything
You Don't Own Your Data
"Can You Please Not"
References
Greenwood, S., Perrin, A. and Duggan, M. (2016). Social Media Update 2016. [online] Pew Research Center: Internet, Science & Tech. Available at: http://www.pewinternet.org/2016/11/11/social-media-update-2016/ [Accessed 7 Aug. 2017].
Kramer, A., Guillory, J., & Hancock, J. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedings Of The National Academy Of Sciences, 111(24), 8788-8790. http://dx.doi.org/10.1073/pnas.1320040111
Pew Research Center: Internet, Science & Tech. (2017). Social Media Fact Sheet. [online] Available at: http://www.pewinternet.org/fact-sheet/social-media/ [Accessed 7 Aug. 2017].
TECHNIQUES FOR EMOTION DETECTION AND CONTENT DELIVERY - FACEBOOK, INC.. (2017). Freepatentsonline.com. Retrieved 28 July 2017, from http://www.freepatentsonline.com/y2015/0242679.html
Kramer, A., Guillory, J., & Hancock, J. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedings Of The National Academy Of Sciences, 111(24), 8788-8790. http://dx.doi.org/10.1073/pnas.1320040111
Pew Research Center: Internet, Science & Tech. (2017). Social Media Fact Sheet. [online] Available at: http://www.pewinternet.org/fact-sheet/social-media/ [Accessed 7 Aug. 2017].
TECHNIQUES FOR EMOTION DETECTION AND CONTENT DELIVERY - FACEBOOK, INC.. (2017). Freepatentsonline.com. Retrieved 28 July 2017, from http://www.freepatentsonline.com/y2015/0242679.html