User:Whimspeck/newsandbox
Datafication
[edit]Datafication is a technological process that transforms daily interactions of technology users to be rendered into a data format.[1][2] First coined by Kenneth Cukier and Viktor Mayer-Schöenberger in 2013, it generates a new form of quantifiable value that can be put to social and enterprising use.Cite error: There are <ref> tags on this page without content in them (see the help page).[2][1] It is considered the conversion of qualitative aspects of life into quantified data.[3] As datafication is the process of tracking aspects of everyday life into quantified online data, it allows for real-time tracking and predictive analysis.[2][1] Such aspects of societal interactions were previously considered qualitative as it was impossible to track detailed social movement.[4] However, this changed with the advent of social media, smartphones and wearable technology. The process of datafication has allowed organisations and enterprises to convert such data into new forms of value.[1][2]
Examples
[edit]The prevalence of self-reporting on social media leads users to provide intimate details. Market research companies use a method called ‘scraping’ to obtain and create detailed profiles of people and groups of people relating to brands, social issues, products, services and political leaning using the details provided on social media platforms.[5][6]
Speech datafication
[edit]The use of speech analytics software is more prevalent as conversations are increasingly recorded and stored as part of interactions with call centres, as well as with other users.[7] The range of voice-based data and meaning is improving, leading to the possibility for conversations to be captured in intelligible format.[4][8]
Data obtained from social media, smartphones and apps is replacing personality tests typically used for job recruitment.[9] The data is used to identify potential employees and their characteristics to match suitability for a position. The use of this data is changing the way personality measuring and testing will be developed.[10]
New CRM techniques using datafication allows a company to manage and analyse its interactions with its past, current and potential customers.[9] This is for the purpose of improving business relationships with their customers and is done by obtaining from the language and tone of voice used within emails, phone calls and social media interaction.[3][2]
Datafication is used in smart cities from data collected by sensors that are implemented into the city.[11][12] This is a means to track and manage issues such as transportation congestion, waste management, logistics and energy generation and consumption in real-time. Sensors that can measure air and water quality can obtain a detailed understanding of pollution levels and may enable new environmental regulations based on real-time data.[11][12]
Impact and issues
[edit]Social and political impact
[edit]The use of datafication can produce certain forms of acting and knowing in the world. One example of this is the Cambridge Analytica scandal surrounding the 2016 US presidential election. British marketing firm Cambridge Analytica illegitimately acquired data from millions of unknowing and non-consenting Facebook users and used it to contribute to US President Trump’s 2016 election campaign.[13][14][15] This was done by displaying certain news articles and content to some users and different content to others.[13][15][14]The scandal sparked debate and awareness on the lack of privacy protection in social media and forced Facebook to promise drastic reduction of data released through its Application Programming Interface. It is in this way that datafication does not just have power and politics, they help to produce certain forms of acting and knowing.[15][14][13][8]
Currency derived from datafication
[edit]Metadata and data derived from the process of datafication has become a currency for users to pay for their means of access to the public world such as communication services, GPS mapping and some forms of security.[2] Few people are aware of or care about the use of their data so there is little to no regulation for how the currency is derived or used.[4][1][2] For this reason, there is a rising trend of data activism; groups or individuals who cooperate to address data privacy concerns.[16]
Cognitive incapacity to make sense of data
[edit]Datafication is a powerful tool to process and store large volumes of data. However, assessing implications still falls to humans and their capacity to make sense of it.[5][3] Sense making is the process of deriving meaning from experience which is currently a challenge for humans and computers.[2][13]
See also
[edit]- Data science
- Digitization/ Digitalization
- Digital transformation
- Big data
- Ethics of artificial intelligence
- Big data ethics
- Machine learning
- Mass surveillance
References
[edit]- ^ a b c d e Mayer-Schönberger, V. and Cukier, K., 2013. Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt.
- ^ a b c d e f g h Van Dijck, J., 2014. Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & society, 12(2), pp.197-208.
- ^ a b c Bazeley, P., 2006. The contribution of computer software to integrating qualitative and quantitative data and analyses. Research in the Schools, 13(1), pp.64-74.
- ^ a b c Ruckenstein, M. and Schüll, N.D., 2017. The datafication of health. Annual Review of Anthropology, 46, pp.261-278.
- ^ a b Bucher, T., 2018. If... then: Algorithmic power and politics. Oxford University Press.
- ^ Marres, N. and Weltevrede, E., 2013. Scraping the social? Issues in live social research. Journal of cultural economy, 6(3), pp.313-335.
- ^ Munzert, S., Rubba, C., Meißner, P. and Nyhuis, D., 2014. Automated data collection with R: A practical guide to web scraping and text mining. John Wiley & Sons.
- ^ a b Isaak, J. and Hanna, M.J., 2018. User data privacy: Facebook, Cambridge Analytica, and privacy protection. Computer, 51(8), pp.56-59.
- ^ a b Sexton, T., Brundage, M.P., Hoffman, M. and Morris, K.C., 2017, December. Hybrid datafication of maintenance logs from ai-assisted human tags. In 2017 ieee international conference on big data (big data) (pp. 1769-1777). IEEE.
- ^ Leurs, K. and Shepherd, T., 2017. 15. Datafication & Discrimination. The Datafied Society, 211.
- ^ a b Bibri, S.E., 2019. The anatomy of the data-driven smart sustainable city: instrumentation, datafication, computerization and related applications. Journal of Big Data, 6(1), p.59.
- ^ a b Calvo, P., 2020. The ethics of Smart City (EoSC): moral implications of hyperconnectivity, algorithmization and the datafication of urban digital society. Ethics and Information Technology, 22(2), pp.141-149.
- ^ a b c d Laterza, V., 2018. Cambridge Analytica, independent research and the national interest. Anthropology Today, 34(3), pp.1-2.
- ^ a b c Venturini, T. and Rogers, R., 2019. “API-Based Research” or How can Digital Sociology and Journalism Studies Learn from the Facebook and Cambridge Analytica Data Breach. Digital Journalism, 7(4), pp.532-540.
- ^ a b c Cadwalladr, C. and Graham-Harrison, E., 2018. ao Cambridge Analytica: links to Moscow oil firm and St Petersburg university. Sat, 17, pp.17-59.
- ^ Milan, S. and Van der Velden, L., 2016. The alternative epistemologies of data activism. Digital Culture & Society, 2(2), pp.57-74.
External links
[edit]- "Digitization, digitalization and digital transformation: the differences". i-SCOOP. 2016-07-25. Retrieved 2019-06-17.
- "From digitization to datafication. A new challenge is approaching archaeology".
Category:Information science Category:Technology forecasting Category:Data management Category:Big data Category:Information society