According to Kortz, using social listening to target residents based on political or racial indicators violates the Equal Protection Clause, a Constitutional guarantee of equal protection under the law. Before the dawn of the Digital Age, there was an oft-used expression, “I’m an open book,” meaning it’s easy to know what someone is feeling or thinking because they hide nothing. Prior to that, Chris was a Research Assistant/Writer for Data-Smart City Solutions. Yet a trickier issue is how to manage situations where some racial or ethnic group is indeed more likely to commit a crime, not just more likely to be targeted by police. As an example of what to do with potentially incriminating data, Kortz pointed to Johnson County, KS. “Beyond questions about what the First Amendment prohibits, there’s much more room to talk about what is good governance and good policy. However, what this article does offer is that identifying threats of crime using good data rather than police intuitions can in fact reduce bias in policing, that keeping considerations of bias in mind while developing such initiatives will ensure continual improvement, and that cities need to have conversations about perpetuating bias before deploying these kinds of initiatives. The second is the scope of the intelligence gathering. This way, cities could ensure that residents understand and have provided input on social mining programs before deploying them. Using social media mining that leverages advances in natural language processing and machine learning to pull useful data from text and images, cities can transform these social posts into data points ripe for analysis. For example, Twitter users might be the first to report on a chemical plant explosion but they’re not likely going to know what exactly exploded that’s turning them into an army of clown-faced zombies. The rise of social media empires like Facebook and Twitter means that millions, if not billions, of our fellow humans are an open book these days. "But, in the meantime, it’s not appropriate for organizations to be taking advantage of information asymmetries." Dataminr notified its clients of the blast about 90 minutes before the official word came in from the gas company. Big Data: Big Brother or Bigger Than Any of Us. Publishing performance data so citizens can assess the effectiveness of practices. In some cases, these outcomes may be a result of historically racist police tactics. These are also the same people who probably drive windowless cargo vans filled with shiny toys. From pictures of emergency conditions to posts about crimes in progress, users constantly inundate Facebook, Instagram, Twitter, and other platforms with posts that may contain rich and timely information about events relevant to public safety. Was there any independence in the testing?” he said. The early warning from Dataminr gave its clients time to react before the market moved. Social networks have become a part of human life. Chris Bousquet is a PhD student in philosophy at Syracuse University. In 2017, in a short series of investigative pieces between The Verge and MapLight, more details emerged about how Dataminr allegedly offered its. Social media in the past started merely as … The increasing availability of data on users and their online behaviour, the decreasing cost of collecting, storing and processing data, and the exponential expansion of social media platforms from which much of this data is taken mean that – at least in theory – an increasingly diverse range of actors can mine social data. The county partnered with researchers from the University of Chicago to develop an early intervention system for individuals who cycle through the criminal justice, mental health, social services, and emergency services systems. “We have to remember why we put so much weight on free speech,” she said. As you might expect, Dataminr has quite the A-list cast of investors, with Morgan Stanley, Fidelity and Goldman Sachs among the more-than-20 backers posted on Crunchbase. When implementing social media mining initiatives then, governments should focus on targeting publicly available posts and institute clear guidelines to ensure their surveillance stays within legal limitations. Platforms like GeoFeedia and a similar tool called Snaptrends tied in dummy accounts—fake profiles that often use provocative pictures of women to attract suspects as friends or followers—to track users’ location across social media sites, regardless of whether or not they publicly geo-tag their posts. “The important questions are does it work? As we are living in a digital world, data … On the surface, it sounds pretty simple: Dataminr aggregates social media data in real-time, including upwards of 500 million tweets per day, and uses machine learning to identify and deliver relevant news to its clients before the breaking news headline hits CNN (though CNN is a media partner). Looking for “Islamist extremist terminology,” the BPD targeted keywords including “ISIS” and “Islamic State,” but also phrases like #MuslimLivesMatter” and “ummah,” the Arabic word for community. According to Mason Kortz——when implementing such initiatives, governments must be cautious not to violate “reasonable expectation of privacy.” Reasonable expectation of privacy is a Constitutional term derived from the Fourth Amendment that protects citizens from warrantless searches of places in which they have a subjective expectation of privacy that is deemed reasonable in public norms. Chris holds a bachelor’s degree from Hamilton College. The company serves five broad industries: finance, corporate security, public sector (including law enforcement), news and public relations. Data mining is a fantastic tool that can extract predictive knowledge from this readily available source of consumer insight. In fact, Cate's proposition that governments should ensure residents are comfortable with data mining initiatives is inherently linked with Kortz's objections on the grounds of reasonable expectation of privacy. The company’s algorithms can reportedly discern fake news from real news because the signals that come in during an actual emergency usually include details such as photos, TechCrunch reported. In that case, there wasn’t much H&M could do, as it lost celebrity endorsements, while stores in South Africa were vandalized. “If a government was trying to defend a policing action against accusations of the chilling effect, they’d have to bring evidence showing they’d been able to police more efficiently,” said Seltzer. Some might read this as an indictment of general social media mining initiatives, requiring suspicion of an individual in order to monitor his or her social media. “A department says, ‘Here’s what we want to do with this algorithm’ and then you have a group—either internal or including community members—examine the proposal,” Cate explained. . By Following the revelation of these practices, Facebook, Twitter, and Instagram revoked access to back-end data for major social mining companies GeoFeedia, SnapTrends, and Media Sonar. As long as people are willing to give away their data for free, there are plenty of companies out there willing to monetize it. Do you target these residents, put them in jail, and perpetuate systems that have made it so that these groups are more likely to commit these crimes? One could imagine these cases of mistaken identity leading to unnecessary escalation. “A policy might have a chilling effect on legitimate speech, but how does this balance out against the legitimate interest of the government to, for instance, protect against violence?” asked Wendy Seltzer. Last month, Stephen Goldsmith and I wrote an article for CityLab detailing transparency requirements the city should consider. Social media data mining is on the rise. The chilling effect describes the result of an indirect discouragement of free speech. take pictures or videos and spread the information into the crowd. 1.2. He made that comment at Bloomberg Global Business Forum and someone tweeted that little nugget, which Dataminr’s algorithms detected, alerting newsrooms to what would become a viral and rankings-boosting news story for little-known news sites like Inverse.com. These social network data mining provide an opportunity to make changes in education system … For Kortz, targeting terms like #blacklivesmatter is a paradigmatic example of racial profiling—identifying people as suspects based on their race. According to Kortz, this is a critical question for governments with social monitoring strategies. Spigit … I. This Constitutional standard requires that the government action does not result in outcomes irrelevant to the stated goal and that it does accomplish the essential aspects of the goal. It removes the need for marketing based on instinct alone.With social media analytics, businesses can … Required fields are marked *. “I’m personally sympathetic to the mosaic theory, but the Court has not been,” he explained. Using social media mining that leverages advances in natural language processing and machine learning to pull useful data from text and images, cities can transform these social posts into data… Similarly, according to Kortz, “In the case of social media, most people expect that only a couple of their friends view their Facebook profiles, but considering the potential for social media mining, there’s a gap between what people expect and what is possible… Expectations define privacy, but they often lag behind reality.”. Reminiscent of the recent Cambridge Analytica controversy, these law enforcement agencies partnered with third parties like GeoFeedia that gained access to backend data streams via APIs. April 26, 2018. For example, last December, an explosion ripped through a major natural gas facility in Austria. Cate even proposed that governments create an institutional review board to assess their data collection efforts. As one example, the City of Huntington Beach, CA used social media monitoring to inform its policing efforts during the U.S. Open of Surfing in 2015, an event that often leads to increased crime along with the large crowds it attracts. 2.Data Integration: combine multiple data sources 3.Data Selection: select the part of the data that are relevant for the problem 4.Data Transformation: transform the data into a suitable format (e.g., a single table, by summary or aggregation operations) 5.Data Mining… Cate however offered that this may not be particularly important. Using social media mining that leverages advances in natural language processing and machine learning to pull useful data from text and images, cities can transform these social posts into data points ripe for analysis. But something like a space-based radar can perform an analysis of the atmosphere in real-time, adding an additional layer of information before the world turns into a post-apocalyptic hellscape. Usually, cities employ algorithms developed by private contractors who are unwilling to release detailed information for fear of revealing proprietary information to competitors, and cities are hesitant to release source code because of concerns over cybersecurity and opportunities to game public systems. 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