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, 2015From Opposing Viewpoints in ContextAndre Oboler is chief executive officer of the Online Hate Prevention Institute and a postgraduate lawstudent at Monash University. Kristopher Welsh is a lecturer in the School of Computing at theUniversity of Kent. Lito Cruz is a teaching associate at Monash University and a part-time lecturer atCharles Sturt University. He holds a PhD in computer science from Monash University. Social media data can be used to collect information about individuals by governments,businesses, journalists, employers, or social media platforms themselves. This data collectioncan result in numerous kinds of infringements of privacy . It could be used to manipulatevoters, track activists, profile job applicants, or even reveal a user's physical movements.Social media platforms have given little consideration to the ethical issues raised. More needsto be done by both social media companies and users to prevent abuses of data.Computational social science involves the collection, retention, use and disclosure of information toanswer enquiries from the social sciences. As an instrument based discipline, the scope ofinvestigation is largely controlled by the parameters of the computer system involved. Theseparameters can include: the type of information people will make available, data retention policies, theability to collect and link additional information to subjects in the study, and the processing ability of thesystem. The capacity to collect and analyze data sets on a vast scale provides leverage to revealpatterns of individual and group behaviour.The revelation of these patterns can be a concern when they are made available to business andgovernment. It is, however, precisely business and government who today control the vast quantitiesof data used for computational social science analysis.Some data should not be readily available: this is why we have laws restricting the use of wiretaps,and protecting medical records. The potential damage from inappropriate disclosure of information issometimes obvious. However, the potential damage of multiple individually benign pieces ofinformation being combined to infer, or a large dataset being analysed to reveal, sensitive information(or information which may later be considered sensitive) is much harder to foresee. A lack oftransparency in the way data is analysed and aggregated, combined with a difficulty in predictingwhich pieces of information may later prove damaging, means that many individuals have littleperception of potential adverse effects of the expansion in computational social science. The risk posed by the ubiquity of computational social science tools ... poses seriousquestions about the impact that those who control the data and the tools can have on societyas a whole.Both the analysis of general trends and the profiling of individuals can be investigated through social sciences. Applications of computational social science in the areas of social anthropology and politicalscience can aid in the subversion of democracy. More than ever before, groups or individuals can beprofiled, and the results used to better manipulate them. This may be as harmless as advertising for aparticular product, or as damaging as political brainwashing. At the intersection of these examples,computational social science can be used to guide political advertising; people can be sold messagesthey will support and can be sheltered from messages with which they may disagree. Access to datamay rest with the incumbent government, with those able to pay, or with those favoured by powerfuldata-rich companies.Under its new terms of service, Google could for instance significantly influence an election bypredicting messages that would engage an individual voter (positively or negatively) and then filteringcontent to influence that user's vote. The predictions could be highly accurate making use of a user'se-mail in their Google provided Gmail account, their search history, their Google+ updates and socialnetwork connections, and their online purchasing history through Google Wallet, data in theirphotograph collection. The filtering of information could include "recommended" videos in YouTube;videos selectively chosen to highlight where one political party agrees with the user's views and whereanother disagrees with them. In Google News, articles could be given higher or lower visibility to helpsteer voters into making "the right choice".Such manipulation may not be immediately obvious; a semblance of balance can be given with anequal number of positive and negative points made against each party. What computational socialscience adds is the ability to predict the effectiveness of different messages for different people. Amessage with no resonance for a particular voter may seem to objectively provide balance, while inreality making little impact. Such services could not only be sold, but could be used by companiesthemselves to block the election of officials whose agenda runs contrary to their interests.The ability to create such detailed profiles of individuals extends beyond the democratic process. Therisk posed by the ubiquity of computational social science tools, combined with an ever-increasingcorpus of data, and free of the ethical restrictions placed on researchers, poses serious questionsabout the impact that those who control the data and the tools can have on society as a whole.Traditionally, concerns about potential abuses of power focus on government and how its power canbe limited to protect individuals; that focus needs to widen.Social media systems contain particularly valuable information. This data derives its value from itsdetail, personal nature, and accuracy. The semi-public nature of the data means it is exposed toscrutiny within a user's network; this increases the likelihood of accuracy when compared to data fromother sources. The social media data stores are owned and controlled by private companies.Applications such as Facebook , LinkedIn, and the Google suite of products (including Google search,YouTube, DoubleClick and others), are driven by information sharing, but monetized through internalanalysis of the gathered data—a form of computational social science. The data is used by four classes of users: business clients, government, other users within the social media platform, and theplatform provider itself.Business clients draw on this computational social science when they seek to target theiradvertisements. Facebook, for example, allows advertisers to target users based on variables thatrange from standard demographics such as age, gender, and geographical location to more personalinformation such as sexual preferences. Users can also be targeted based on interests, associations,education level and employer. The Facebook platform makes this data (in aggregated form) availableto advertisers for a specific purpose, yet Facebook's standard user interface can also be used as ageneral computational social science tool for other purposes. The very existence of social media can ... promote government's agenda.To take an example, the Australian Bureau of Statistics (ABS) estimates the current population ofAustralia at 22.5 million. The Facebook advertising platform gives an Australia population (onFacebook) of 9.3 million; over 41 percent of the national population. As there is less coverage at thetails, Facebook has only 0.29 million people over 64, while the ABS says there are 3.06 millionAustralians over 65, the sample for some age ranges must be approaching the entire population andmay provide a very good model as a computational social science tool. For example, research showsthat about two percent of the Australia population is not heterosexual. From the Facebook advertisingplatform, we can readily [select] a population of Australians, aged 18 to 21, who are male, and whosesexual preference is for men. The platform immediately tells us the population size is 11,580 people.By comparing this to the total size of the Australian male Facebook population who expressed asexual preference, we can see this accounts for 2.89 percent of this population, indicating that thedata available to Facebook is of similar utility to that available to social scientists for research.The second class of users of social media as computational social science tools is governmental. Thisis demonstrated by the U.S. government's demands to Twitter (via court orders) for data on Wikileaksfounder Julian Assange and those connected to him. The court order was only revealed after Twittertook legal action to lift a court imposed censorship order relating to the requests. The Wikileaks affairdemonstrates how government can act when it sees social media as acting against its interests.The very existence of social media can also promote government's agenda. During the Iranianelections, for example, Twitter was asked not to take their service off-line for scheduled maintenance.In another example, the U.S. State Department provided training "using the Internet to effect socialchange " to Egyptian dissidents between 2008 and 2010, then sought (unsuccessfully) to keep socialmedia access available during the January 2011 Egyptian anti-government protests. The Egyptianeffort was defeated after Egypt responded by taking the entire country off the Internet, a move perhapsmore in response to the U.S. than the protestors. While social media might enable activism,computational social science favours the state or at least those with power. Computational socialscience tools combined with social media data can be used to reconstruct the movements of activists,to locate dissidents, and to map their networks. Governments and their security services have a stronginterest in this activity. The third class of actors are other social media platform users. Journalist Ada Calhoun has describedas an epiphany that left her "freaked out" the realisation that anyone could research her just as sheresearched others while writing their obituaries. In her article, Calhoun reflected that some amateurexperts on the anarchic message board 4chan, or professional experts working for governmentagencies, could likely find out far more than she could. The everyday danger that can result whenanyone can research anyone else can be demonstrated through two scenarios: Scenario one involves Mary who has been a Facebook user for some years. ThroughFacebook Mary reconnected with an old friend Fred. As time went on, Mary and Fred grewcloser and became a couple. One day Mary logged into her Facebook account and noticedthat Fred has still not updated his details to say he is in a relationship with her. This makesMary feel very insecure, and causes her to begin doubting Fred's intentions. Due to thisdiscovery, Mary broke off her relationship with Fred.Joe applied to a company as a Human Resource team leader. The hiring manager, Bob, foundJoe's resume appealing and considered him a good candidate. Bob decides to check Joe'sFacebook information. On Joe's publically viewable wall, Bob sees several pictures of Joe inwhat Bob considers to be "questionable settings". The company never called Joe for aninterview. Joe has been given no opportunity to explain, nor any explanation on why hisapplication was rejected.Computational science can help a company like Facebook correctly profile its users, showingthe right advertisements to the right people so as to maximize revenue.Both Mary and Bob used Facebook as a computational tool to extract selected information as part ofan investigation into the social dynamics of society, or in these cases, a particular individual'sinteractions with society. In this sense, Facebook could be considered a computational social sciencetool. Mary's inference may be based on a wider realisation that Fred's interactions with her are all inprivate and not part of his wider representation of himself. Bob may have drawn his conclusions from acombination of text, pictures, and social interactions.These situations are far from hypothetical. Research released in November 2011 by Telstra,Australia's largest telecommunications company, revealed that over a quarter of Australian bosseswere screening job candidates based on social media. At the start of 2012 the Australia Federal Policebegan an advertising campaign designed to warn the public of the need to protect their reputationonline. The advertisement featured a job interview where the interviewer consults a paper resume thenproceeds to note various positive attributes about the candidate; all seems to be going very well. Theinterviewer then turns to his computer screen and adds "and I see from your recent online activity youenjoy planking from high rise buildings, binge drinking, and posting embarrassing photos of yourfriends online". The advertisement is an accurate picture of the current approach, which takes place atthe level of one user examining another. Computational social science may soon lead to softwareprograms that automatically complete pre-selection and filtering of candidates for employment.The final class or actor we consider are social media platform providers themselves. While Facebookprovides numerous metrics to profile users for advertisers, far more data and scope for analysis isavailable to a platform provider like Facebook itself. Internet advertisements are often sold on a "cost per-click" (CPC) or "cost per-impression" (CPM—with M indicating costs typically conveyed per-thousand impressions). Thus, Facebook may maximize advertising revenue by targetingadvertisements to achieve the greatest possible number of clicks for a given number of impressions.This maximization of the click-through rate (CTR) can be achieved using a wealth of hiddeninformation to model which users are most likely to respond to a particular advertisement.Computational science can help a company like Facebook correctly profile its users, showing the rightadvertisements to the right people so as to maximize revenue. But what else can a company likeFacebook or Google do? This depends on the data they hold.While horizontal expansion of computational social science allows greater access to selectedaggregate data, vertical expansion allows larger operators to add depth to their models. This depth isa result of triangulation, a method originally from land surveying. Triangulation gives a confirmationbenefit by using additional data points to increase the accuracy and confidence in a measurement. Ina research context triangulation allows for information from multiple sources to be combined in a waythat can expose underlying truths and increase the certainty of conclusions.Social media platforms have added to their data either by acquiring other technology companies, asGoogle did when acquiring DoubleClick and YouTube, or by moving into new fields as Facebook did inwhen it created "Facebook Places": a foursquare-like geolocation service. From a computational socialscience perspective, geolocation services in particular add high value information. Maximising thevalue of information requires a primary key that connects this data with existing information; aFacebook user ID, or a Google account name provides just such a key.The measures how many types of online interaction the one account connects.It lets the company providing the account know about a wider slice of a user's life. Three situations arepossible. The first involves distinct accounts on multiple sites and allows no overlap of data: whatoccurs on one site stays on that site. The second situation is where there is a single traceable login,for example your e-mail address, which is used on multiple sites but where the sites are independent.Someone, or some computational social science tool, with access to the datasets could aggregate thedata. The third possibility is a single login with complete data sharing between sites. All the data isimmediately related and available to any query the underlying company devises. It is this last scenariothat forms the Holy Grail for companies like Facebook and Google, and causes the most concern forusers.The announcement by Alma Whitten, Google's Director of Privacy, Product and Engineering inJanuary 2012 that Google would aggregate its data and "treat you as a single user across all ourproducts" has led to a sharp response from critics. Jeffrey Chester, executive director of the Center forDigital Democracy, told the : "There is no way a user can comprehend the implicationof Google collecting across platforms for information about your health, political opinions and financialconcerns." In the same article, Common Sense Media chief executive James Steyer states bluntly that"Google's new privacy announcement is frustrating and a little frightening". Accounts that are identity-verified, frequently updated, and used across multiple aspects of a person's life present the richest data and pose the greatest risk.The measures the amount of data an account connects. There are three possiblesituations. The first is an anonymous login with no connection to personal details, the virtual profile iscomplete in and of itself—it may or may not truthfully represent the real world. The second situation isan account where user details are verified, for example a university login that is only provided once astudent registers and identification papers have been checked. A number of online services and virtualcommunities are now using this model and checking government issued identification to verify age.The third situation involves an account that has a verified identity aggregated with other data collectedfrom additional sources, for example, a credit card provider knows who its customers are, as well aswhere they have been and what they have bought. The temporal nature of the data is also a matter ofdepth; your current relationship status has less depth than your complete relationship history.Facebook's Timeline feature signifies as large a change to depth as Google's policy change does tobreadth. Timeline lets users quickly slide to a previous point in time, unearthing social interactions thathad long been buried. A Facebook announcement on 24 January 2012 informed the world thatTimeline was not optional and would in a matter of weeks be rolled out across all Facebook profiles.As Sarah Jacobsson Purewal noted in , with Timeline it takes only a few clicks to see datathat previously required around 500 clicks on the link labelled "older posts", each click separated by afew seconds delay while the next batch of data loads. Purewal provides a step-by-step guide toreasserting privacy under the new timeline regime, the steps are numerous and the ultimateconclusion is that "you may want to just consider getting rid of your Facebook account and startingfrom scratch". Though admittedly not scientific, a poll by Sophos, an IT security and data protectioncompany, showed that over half those polled were worried about Timeline. The survey included over4,000 Facebook users from a population that is likely both more concerned and more knowledgeableabout privacy and security than the average user. If that wasn't telling enough, the author of theannouncement, Sophos' senior technology consultant, Graham Cluley, announced in the same articlethat he had shutdown his Facebook account. Cluley's reasoning was a response to realizing exactlyhow much of his personal data Facebook was holding, and fatigue at Facebook's ever changing andnon-consultative privacy regime.All accounts have both a breadth and a depth. Accounts that are identity-verified, frequently updated,and used across multiple aspects of a person's life present the richest data and pose the greatest risk.The concept of a government-issued national identity card has created fierce debate in manycountries, yet that debate has been muted when the data is collected and held by non-governmentactors. Google's new ubiquitous account and Facebook's single platform for all forms of socialcommunication should raise similar concerns for individuals as both consumers and citizens....In discussing the ethics of social science research, [Constance] Holden noted two schools of thought:utilitarianism (also known as consequentialism) holds that an act can only be judged on itsconsequences; deontologicalism (also known as non-consequentialism) is predominantly aboutabsolute moral ethics. In the 1960s utilitarianism was dominant, along with moral relativism; in the late 1970s deontologicalism began to hold sway. In computational social science, the debate seems to beacademic with little regard given to ethics. Conditions of use are typically one-sided without user input,although Wikipedia is a notable exception. Companies expand their services and data sets with littleregard for ethical considerations, and market forces in the form of user backlashes [are] the first, andoften only, line of resistance.One such backlash occurred over Facebook's Beacon software, which was eventually cancelled aspart of an out of court settlement. Beacon connected people's purchases to their Facebook account; itadvertised to their friends what a user had purchased, where they got it, and whether they got adiscount. In one instance, a wife found out about a surprise Christmas gift of jewellery after herhusband's purchase was broadcast to all his friends—including his wife. Others found their videorentals widely shared, raising concerns it might out people's sexual preferences and other details oftheir private life. 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COPYRIGHT 2015 Greenhaven Press, a part of Gale, Cengage Learning. Oboler, Andre, et al. "Social Media Data Collection Can Lead to Violations of Privacy." , edited by Noah Berlatsky, GreenhavenPress, 2015. At Issue. , ezproxy.snhu.edu/login?url=http://link.galegroup.com/apps/doc/EJ3010744218/OVIC?u=nhc_main&xid=e1f1f0a0 . Accessed 22 June 2017. Originally published as "TheDanger of Big Data: Social Media as Computational Social Science," , vol. 17, no. 7, 2 July 2012. GALE|EJ3010744218