Datafication is a technological trend turning many aspects of our life into data which is subsequently rendered into information realised as a new form of value. [1] Kenneth Cukier and Viktor Mayer-Schönberger introduced the term datafication to the broader lexicon in 2013. [1] Up until this time, datafication had been associated with the analysis of representations of our lives captured through data, but not on the present scale. This change was primarily due to the impact of big data and the computational opportunities afforded to predictive analytics. The drastic proliferation of smartphones and wearable technologies enabled the capacity to track and render detailed societal interactions into quantified data. [2] Before then, detailed collection and analysis of societal interactions were previously observed via qualitative methods. [2] The value rendered from the process of datafication holds form as a commodity and, in some cases, an online currency. [3]
Self-reporting on social media and the prevalence of shared personal details have led to market research companies adopting methods of data scraping to obtain and create detailed profiles of groups of users that can relate to their sentiments toward social issues, political leaning, products and services. [3] The findings and resulting profiles can then be used or sold to assist companies or organizations in understanding reaching their target market or clientele. [4]
Data obtained from mobile phones, apps or social media usage can be used to identify potential employees and their specific characteristics such as generating a risk taking and personality profile, rather than using traditional personality tests or exams that measure analytical thinking. [5] [6] These methods have replaced some existing exam provider operations, typically used for recruitment to identify potential employees, as well as the pre-existing personality measures and their future development. [5] [2]
Datafication is used in smart cities from data collected by sensors that are implemented into the city. This enables the tracking of arising issues such as transportation congestion, waste management, logistics and energy generation and consumption in real-time. [8] [9] Sensors that measure air and water quality can obtain a detailed understanding of pollution levels and may enable new environmental regulations based on real-time data. [8]
In the Cambridge Analytica scandal surrounding the 2016 US presidential election, US marketing firm Cambridge Analytica illegitimately acquired data from millions of unknowing Facebook users and used it to contribute to former US President Donald Trump’s 2016 election campaign. [10] [11] [12] Enacted by displaying selected news articles and content to some users and different or opposing content to others. [13] The scandal sparked debate and awareness on the lack of privacy protection on social media and forced Facebook, Inc. to promise drastic reduction of data released through its Application Programming Interface. [14] [15]
Metadata and data derived from the process of datafication have become a currency for users to pay for their means of access to the public world. [16] [2] Such as with communication services, GPS mapping and some forms of security. [17] Few people are aware of the use of their data so there is little to no regulation for how such currency is derived or used. For this reason, there is a rising trend of data activism; groups or individuals who cooperate to address data privacy concerns. [18] [19]
{{
cite web}}
: CS1 maint: url-status (
link)
{{
cite web}}
: CS1 maint: url-status (
link)
Datafication is a technological trend turning many aspects of our life into data which is subsequently rendered into information realised as a new form of value. [1] Kenneth Cukier and Viktor Mayer-Schönberger introduced the term datafication to the broader lexicon in 2013. [1] Up until this time, datafication had been associated with the analysis of representations of our lives captured through data, but not on the present scale. This change was primarily due to the impact of big data and the computational opportunities afforded to predictive analytics. The drastic proliferation of smartphones and wearable technologies enabled the capacity to track and render detailed societal interactions into quantified data. [2] Before then, detailed collection and analysis of societal interactions were previously observed via qualitative methods. [2] The value rendered from the process of datafication holds form as a commodity and, in some cases, an online currency. [3]
Self-reporting on social media and the prevalence of shared personal details have led to market research companies adopting methods of data scraping to obtain and create detailed profiles of groups of users that can relate to their sentiments toward social issues, political leaning, products and services. [3] The findings and resulting profiles can then be used or sold to assist companies or organizations in understanding reaching their target market or clientele. [4]
Data obtained from mobile phones, apps or social media usage can be used to identify potential employees and their specific characteristics such as generating a risk taking and personality profile, rather than using traditional personality tests or exams that measure analytical thinking. [5] [6] These methods have replaced some existing exam provider operations, typically used for recruitment to identify potential employees, as well as the pre-existing personality measures and their future development. [5] [2]
Datafication is used in smart cities from data collected by sensors that are implemented into the city. This enables the tracking of arising issues such as transportation congestion, waste management, logistics and energy generation and consumption in real-time. [8] [9] Sensors that measure air and water quality can obtain a detailed understanding of pollution levels and may enable new environmental regulations based on real-time data. [8]
In the Cambridge Analytica scandal surrounding the 2016 US presidential election, US marketing firm Cambridge Analytica illegitimately acquired data from millions of unknowing Facebook users and used it to contribute to former US President Donald Trump’s 2016 election campaign. [10] [11] [12] Enacted by displaying selected news articles and content to some users and different or opposing content to others. [13] The scandal sparked debate and awareness on the lack of privacy protection on social media and forced Facebook, Inc. to promise drastic reduction of data released through its Application Programming Interface. [14] [15]
Metadata and data derived from the process of datafication have become a currency for users to pay for their means of access to the public world. [16] [2] Such as with communication services, GPS mapping and some forms of security. [17] Few people are aware of the use of their data so there is little to no regulation for how such currency is derived or used. For this reason, there is a rising trend of data activism; groups or individuals who cooperate to address data privacy concerns. [18] [19]
{{
cite web}}
: CS1 maint: url-status (
link)
{{
cite web}}
: CS1 maint: url-status (
link)