Social profiling

The ever-increasing online content has resulted in the lack of proficiency of centralized search engine's results.[6][7] It can no longer satisfy user's demand for information. A possible solution that would increase coverage of search results would be meta-search engines,[6] an approach that collects information from numerous centralized search engines. A new problem thus emerges, that is too much data and too much noise is generated in the collection process. Therefore, a new technique called personalized meta-search engines emerges, which refers to a user's profile (largely social profile) to filter the search results. A user's profile can be a combination of a number of things, including but not limited to, "a user's manual selected interests, user's search history", and personal social network data.[6]

A lot of information are voluntarily shared on online social networks, and many people rest assured that different social network accounts on different platforms won't be linked as long as they don't grant permission to these links. However, according to Diane Gan, information gathered online enabled "target subjects to be identified on other social networking sites such as Foursquare, Instagram, LinkedIn, Facebook and Google+, where more personal information was leaked".[10]

The majority of social networking platforms use the "opt out approach" for their features. If users wish to protect their privacy, it is user's own responsibility to check and change the privacy settings as a number of them are set to default option.[10] A major social network platforms have developed geo-tag functions and are in popular usage. This is concerning because 39% users have experienced profiling hacking; 78% burglars have used major social media networks and Google Street-view to select their victims; an astonishing 54% of burglars attempted to break into empty houses when people posted their statuses and geo-locations.[11]

Formation and maintenance of social media accounts and its relationships with others are associated with various social outcomes.[12] For many firms, customer relationship management is essential and partially done through Facebook.[13] Before the emergence and prevalence of social media, customer identification is primarily functioned upon information that a firm can directly acquire:[14] for example, it may be through a customer's purchasing process or volunteered act of completing a survey/loyalty program. However, the rise of social media has greatly reduced the process of building a customer's profile/model based on such available data. Marketers now greatly seek customer information through Facebook;[13] this may include a variety of information users disclose to all users or partial users on Facebook: name, gender, date of birth, e-mail address, sexual orientation, marital status, interests, hobbies, favorite sports team(s), favorite athlete(s), or favorite music, more importantly Facebook connections.[13]

However, due to the privacy policy design, acquiring true information on Facebook is no trivial task. Often, Facebook users either refuse to disclose true information or set information only visible to friends, Facebook users who "LIKE" your page are also hard to be identified. To do online profiling of users and to cluster users, marketers and companies can and will access the following kinds of data: gender, the IP address and city of each user through the Facebook Insight page, who "LIKED" a certain user, a page list of all the pages that a person "LIKED" (transaction data), other people that a user follow (even if it exceeds the first 500, which we usually can not see)and all the publicly shared data.[13]

First launched on the Internet in March 2006, Twitter is a platform on which users can connect and communicate with any other user in just 140 characters.[10] Like Facebook, Twitter is also a crucial tunnel for users to leak important information, often unconsciously, but able to be accessed and collected by others.

According to Rachel Numer, in a sample of 10.8 million tweets by more than 5,000 users, their posed and publicly shared information are enough to reveal a user's income range.[15] A postdoctoral researcher from the University of Pennsylvania, Daniel Preoţiuc-Pietro and his colleagues were able to categorize 90% of users into corresponding income groups. Their existing collected data, after being fed into a machine-learning model, generated reliable predictions on the characteristics of each income group.[15]

Photo on the right depicts an mobile app called Streamd.in. It displays live tweets on Google Maps by using geo-location details attached to the tweet, and traces the user's movement in the real world.[10]

The advent and universality of social media network have boosted the role of images and visual information dissemination.[16] Many visual information on social media transmits messages from the author, location information and other personal information. In a study done by Cristina Segalin, Dong Seon Cheng and Marco Cristani, they found that profiling user posts' photos can reveal personal traits such as personality and mood.[16] In the study, convolutional neural networks (CNNs) is introduced. It builds on the main characteristics of computational aesthetics CA (emphasizing "computational methods", "human aesthetic point of view", and "the need to focus on objective approaches"[16]) defined by Hoenig (Hoenig, 2005). This tool can extract and identify content in photos.

In a study called "A Rule-Based Flickr Tag Recommendation System", the author suggests personalized tag recommendations,[17] largely based on user profiles and other web resources. It has proven to be useful in many aspects: "web content indexing", "multimedia data retrieval", and enterprise Web searches.[17]

Until 2006, communications online are not content led in terms of the amount of time people spend online. However, content sharing and creating has been the primary online activity of general social media users and that has forever changed online marketing.[20] In the book Advanced Social media Marketing,[21] the author gives an example of how a New York wedding planner might identify his audience when marketing on Facebook. Some of these categories may include: (1) who live in the United States; (2) Who live within 50 miles of New York; (3) Age 21 and older; (4) engaged female.[21] No matter you choose to pay cost per click or cost per impressions/views "the cost of Facebook Marketplace ads and Sponsored Stories is set by your maximum bid and the competition for the same audiences".[21] The cost of clicks is usually $0.5–1.5 each.

Klout is a popular online tool that focuses on assessing a user's social influence by social profiling. It takes several social media platforms (such as Facebook, Twitter etc.) and numerous aspects into account and generate a user's score from 1-100. Regardless of one's number of likes for a post, or connections on LinkedIn, social media contains plentiful personal information. Klout generates a single score that indicates a person's influence.

In a study called "How Much Klout do You Have...A Test of System Generated Cues on Source Credibility" done by Chad Edwards, Klout scores can influence people's perceived credibility.[22] As Klout Score becomes a popular combined-into-one-score method of accessing people's influence, it can be a convenient tool and a biased one at the same time. A study of how social media followers influence people's judgments done by David Westerman illustrates that possible bias that Klout may contain.[23] In one study, participants were asked to view six identical mock Twitter pages with only one major independent variable: page followers. Result shows that pages with too many or too fewer followers would both decrease its credibility, despite of its similar content. Klout score may be subject to the same bias as well.[23]

While this is sometimes used during recruitment process, it remains to be controversial.

Kred not only assigns each user an influence score, but also allows each user to claim a Kred profile and Kred account. Through this platform, each user can view how top influencers engage with their online community and how each of your online action impacted your influence scores.

Keyhole Data Analytics

Several suggestions that Kred is giving to the audience about increasing influence are: (1) be generous with your audience, free comfortable sharing content from your friends and tweeting others; (2) join an online community; (3) create and share meaningful content; (4) track your progress online.

Follower Wonk is specifically targeted towards Twitter analytics, which helps users to understand follower demographics, and optimizes your activities to find which activity attracts the most positive feedback from followers.

Keyhole is a hashtag tracking and analytics device that tracks Instagram, Twitter and Facebook hashtag data. It is a service that allows you to track which top influencer is using a certain hashtag and what are the other demographic information about the hashtag. When you enter a hashtag on its website, it will automatically randomly sample users that currently used this tag which allows user to analyze each hashtag they are interested in.

Although the implementation of social credit score remains controversial in China, Chinese government aims to fully implement this system by 2018.[27] According to Jake Laband (the deputy director of the Beijing office of the US-China Business Council), low credit scores will "limit eligibility for financing, employment, and Party membership, as well restrict real estate transactions and travel." Social credit score will not only be affected by legal criteria, but also social criteria, such as contract breaking. However, this has been a great concern for privacy for big companies due to the huge amount of data that will be analyzed by the system.