词条 | Participatory surveillance |
释义 |
HistoryTowards the beginning of the development of Web 2.0, an increase in online socializing and interaction emerged, largely from the function of social media platforms.[3][4] Social media platforms originally emerged within the context of the online information highway, where users can control what information is available to other users of the platform. Users can now digitally attach people to locations, without having to physically be within the location, a concept coined as geotagging.[3] With added awareness of the locations of users, an aspect of greater socialization and interconnectivity emerges within both the digital and tangible world. Since the online information highway collects and stores information more permanently than the physical world, many interactions amongst online users can last much longer than physical ones. Since users can control the information and locations in which they associate themselves, they can in part surveil themselves and others to an extent. This is participatory surveillance within a web-based paradigm.[3] In contrast to this, participatory surveillance has begun to be referred to as a tool for ecological field research. Currently, it is extremely difficult to detect disease outbreaks in enough time to prepare people for the outcomes. Often, in hard to reach areas such as the Arctic, researchers cannot gain an intensive look into the subject of disease outbreak closely enough to gain accurate results. Indigenous peoples know the ecology of the land better and how to reach overlooked locations of research. Researchers can use these people as rural surveyors, capturing instances of disease outbreak much quicker and easier than the researchers themselves.[5] Social mediaCounter-surveillanceCounter-surveillance refers to the personal monitoring of individuals through means of the online information highway. Through government and corporate surveilling practices, the average person has begun to develop an interest in a type of profiling of friends and others through digital technology.[4] However, this enlightens the fact that the average person does not fully understand the surveilling practices used by larger collectivities. With more training in these capacities, it allows greater accountability and management of how surveillance is used and analyzed in everyday associations.[4] As digital technology advances with many dangers associated to privacy, individuals are attempting to be more accountable when meeting individuals. Background check websites and search engine sources reveal just how many people attempt to find information on another person, whatever the reason. Some researchers assert that by using these technologies of surveillance, the same ones used by companies to track consumer tendencies, the public is essentially feeding into practices of their own personal surveillance.[4] EmpowermentOne argument towards social media based participatory surveillance is participatory surveillance within social digital media schemas work to emphasize the power that comes from monitoring what is surveilled of themselves in the context of others rather than being constituted as an invasion of privacy, or disempowerment.[15] Within the visual discourse of reality television, the artistic narrative associated with presenting lives, creates a fake reality in which people can contextualize, therefore keeping the reality of some aspects of an individual or collectives lives still privatized. This thinking can be transposed to other socially constructed media technologies. In contrast, ambient awareness is associated with cell phones since they are almost always never turned off, through even the most menial of everyday tasks. This poses a greater security risk. Surveillance webcams focus on the aspects of reality users want to show to the digital audience. It is privatized in the respect that users control what they allow others to see causing them to feel liberated.[15] InfodemiologyAn emerging term within social media based participatory surveillance, infodemiology refers to the use of digital based applications or surveys, to better track disease patterns.[1][5][6] Largely using information people search for related to health as well as what the public says on digital-based platforms makes up the fabric of this field of study. Coming about in 2002, infodemiology measures common social media platforms, disease and illness related websites, search engine information, and any other online user-related health data.[6] H1N1 virusTwitter, a user-generated platform for social media, can effectively help track users’ thoughts and opinions on diseases as well as help track disease at a greater rate.[5][7] For example, the H1N1 virus (swine flu) outbreak in 2009 was analyzed through Twitter reactions and responses in order to investigate these areas of thought. After analyzing and comparing tweets through different severities of the H1NI outbreak, the researchers posited that tweets can be a reliable estimate in understanding disease patterns.[8]The speed at which social media reveals public thought and trends is about two weeks faster than that of standardized disease surveillance through the proper health-related institutions. An example of social media reactions related to the H1N1 virus include an increased lack of discussion around antiviral drugs at approximately the same time as the H1N1 virus became less prevalent.[8] However, due to the nature of social media as user-generated and unregulated, deciphering between what is relevant versus irrelevant material can blur generalizations and facts. Along with this, people are wavering and unreliable with when and what they post about on social media. With that, social media is an unstable variable which, in order to become standardized, would require great expense to create measures in which it would become feasible to make valid generalizations about.[8] To elaborate using the example of Twitter, information on sickness can change meaning in a connotative sense. For example, if a user tweets about popular pop artist Justin Bieber saying they have “Bieber Fever,” this is very apparently not a real sickness, but a faux sickness based on the popularity of an artist. This creates issues in organizing information, requiring complex algorithms that can analyze the contours of these social meanings.[9] Nonetheless, a recent study noted that studies focusing on the use of Youtube to detect outbreaks only had a twenty to thirty percent range of error, leading researchers' to continue looking into the prospect of social media as a force for change in disease outbreak.[7] Chikungunya virusChikungunya virus, associated with moderate to severe skin rashes and joint pain, spread to Italy at the beginning of 2007.[10] The outbreak caused great social concern, therefore causing a plethora of social media reactions to emerge. Using an infodemiological approach, the sites where the outbreak was recorded, specifically PubMed, Twitter, Google Trends and News, and Wikipedia views and edits all provided information into when the disease was received, the concerns associated with the outbreak, and popular opinion on the disease. Interestingly, most of the Twitter posts related to Chikungunya were highly guided by search engine queries rather than empirical investigations, leading to non-usable data. Using mediation technology, Wikipedia proved to be ineffective in determining whether the site was helpful in understanding the outbreak. Moreover, users who gained opinions on the outbreak from news sources were similar to the Wikipedia edits and reactions. Similarly, the PubMed responses were consistent with that of the Wikipedia and Twitter responses. Overall, a significant amount of information was gathered from these sources, deeming these sites to be useful in documenting disease and public reaction.[10]Ecological Field WorkCholera OutbreakIn hard to access regions such as the Arctic and rural regions in Canada, researching ecological processes and disease spread can be hard to access without constant monitoring. In these rural, less populated area, indigenous populations may become a key aspect in understanding the spread of disease, due to their proximity and connection to the land.[5] For example, the use of Inuit indigenous peoples in helping to identify outbreak zones of avian cholera. Specifically, the Common Eider, a species of sea duck, was being analyzed in Canada. Using the help of the Inuit peoples, the researchers were able to detect the outbreak of cholera in thirteen locations from 2004 to 2016. The Inuit peoples were able to keep a closer eye on death rates of the Common Eider due to their daily routines throughout the land.[5] Privacy ConcernsAs digital technology advances with many dangers associated to privacy, individuals are attempting to be more accountable when meeting others. Background check websites and search engine sources reveal just how many people attempt to find information on another person, whatever the reason.[4] Many researchers altogether ignore the idea of privacy when analyzing methods of participatory surveillance. More so, from a social media perspective, some researchers claim that by openly sharing information with others, this cannot be deemed a breach of privacy.[11] However, a few researchers on the topic mention breaches of privacy within the spheres of both digital media studies and infodemiology. InfodemiologyInfodemiology relies on users' information to analyze health patterns and public health concerns.[12] However, the legality behind using other people's information without their consent can cause serious ethical privacy violations. However, limitations such as individual privacy concerns and unreliable information cause participatory digital information to sometimes be inaccurate and hard to differentiate from truth.[12] DoxingDoxing is a form of cyberbullying, using the Internet to post private information about an individual or organization as a means of attack against the entity.[13] Common information that can be leaked can be anything from a past discretion, home address, or even social security number of the victim.[13] This information could be freely available on the Internet for the attacker to gain access to and make public. This differentiates it from other types of information leaks, since the information is simply being brought to the forefront of the public's viewing. In other words, the public information being leaked could be found freely by other parties even if it was not exposed in a more public light. The term "doxing" comes from the origins of document, first used in 2001 with the infamous hacker collective called Anonymous.[13] With today's current laws, most legislation pertaining to cyber threats and attacks are rooted in the 1990s, when the Internet was just developing. Due to information being stored online, doxing does not adhere to standard rights of privacy. Constitutionally, individuals should have the right to disclose or not disclose information, while at the same time being able to make decisions about privacy.[13] The Fourth Amendment protects the right to free speech, but doxing uniquely uses information available to the public, leading some 'doxers' to claim that they are simply exercising their Fourth Amendment rights. The only exception to Fourth Amendment rights came about from Cohen v. California, which established the "true threat" exception.[13] This exception established a breach of free speech rights whenever the content of the speech maliciously invades privacy interests. However, this exception may only work in some doxing situations, where the court measures the extent of the offense and the reactions from the attack.[13] See also
References1. ^1 {{Cite journal |last=Velasco |first=Edward |date=2014 |title=Social Media and Internet-Based Data in Global Systems for Public Health Surveillance: A Systematic Review |url= |journal=Milbank Quarterly |volume= |pages= |via=}} {{improve categories|date=November 2018}}2. ^{{Cite journal |last=Wójcik |first=Octawia P. |date=2014 |title=Public Health for the People: Participatory Infectious Disease Surveillance in the Digital Age |url= |journal=Emerging Themes in Epidemiology |volume= |pages=1–14 |via=}} 3. ^1 2 3 4 {{Cite journal |last=Albrechtslund |first=Anders |date=2008 |title=Online Social Networking as Participatory Surveillance |url= |journal=First Monday |volume= |pages= |via=}} 4. ^1 2 3 4 {{Cite journal |last=Andrejevic |first=Mark |date=2002 |title=The Work of Watching One Another: Lateral Surveillance, Risk, and Governance |url= |journal=Surveillance & Society |volume= |pages= |via=}} 5. ^1 2 3 {{Cite journal |last=Iverson |first=Samuel A.|display-authors=etal|date=2016 |title=Avian Cholera Emergence in Arctic-Nesting Northern Common Eiders: Using Community-Based, Participatory Surveillance to Delineate Disease Outbreak Patterns and Predict Transmission Risk |url= |journal=Ecology and Society |volume= |pages= |via=}} 6. ^1 {{Cite journal |last=Eysenbach |first=Gunther |date=2009 |title=Infodemiology and Infoveillance: Framework for an Emerging Set of Public Health Informatics Methods to Analyze Search, Communication and Publication Behavior on the Internet |url= |journal=Journal of Medical Internet Research |volume= |pages= |via=}} 7. ^1 {{Cite journal |last=Tang |first=Lu|display-authors=etal|date=2018 |title=Social Media and Outbreaks of Emerging Infectious Diseases: A Systematic Review of Literature |url= |journal=American Journal of Infection Control |volume= |pages=962–72 |via=}} 8. ^1 2 3 4 5 {{Cite journal |last=Signorini |first=Alessio|display-authors=etal|date=2011 |title=The Use of Twitter to Track Levels of Disease Activity and Public Concern in the U.S. during the Influenza A H1N1 Pandemic |url= |journal=PLOS One |volume= |pages= |via=}} 9. ^{{Cite book |title=Social Media and Health Crisis Communication During Epidemics |last=Syed-Abdul |first=Shabbir|display-authors=etal|publisher=Elsevier/Academic Press |year=2016 |isbn= |location=Amsterdam |pages=42–66}} 10. ^1 {{Cite journal |last=Mahroum |first=Naim|display-authors=etal|date=2018 |title=Public Reaction to Chikungunya Outbreaks in Italy—Insights from an Extensive Novel Data Streams-Based Structural Equation Modeling Analysis |url= |journal=PLOS One |volume= |pages= |via=}} 11. ^1 2 {{Cite journal |last=Koskela |first=Hille |date=2002 |title=Webcams, TV Shows and Mobile Phones: Empowering Exhibitionism |url= |journal=Surveillance and Society |volume= |pages= |via=}} 12. ^1 {{Cite journal |last=Choi|display-authors=etal|first=Jihye |date=2016 |title=Web-Based Infectious Disease Surveillance Systems and Public Health Perspectives: a Systematic Review |url= |journal=BMC Public Health |volume= |pages=1–10 |via=}} 13. ^1 2 3 4 5 {{Cite journal |last=MacAllister |first=Julia M. |date=2017 |title=The Doxing Dilemma: Seeking a Remedy for the Malicious Publication of Personal Information |url=https://ir.lawnet.fordham.edu/flr/vol85/iss5/21/ |journal=Fordham Law Review |volume= |pages= |via=}} 1 : Surveillance |
随便看 |
|
开放百科全书收录14589846条英语、德语、日语等多语种百科知识,基本涵盖了大多数领域的百科知识,是一部内容自由、开放的电子版国际百科全书。