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Social data revolution
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Social data revolution
The social data revolution is the shift in human communication patterns towards increased personal information sharing and its related implications, made possible by the rise of social networks in the early 2000s. This phenomenon has resulted in the accumulation of unprecedented amounts of public data.
This large and frequently updated data source has been described as a new type of scientific instrument for the social sciences. Several independent researchers have used social data to "nowcast" and forecast trends such as unemployment, flu outbreaks, mood of whole populations, travel spending and political opinions in a way that is faster, more accurate and cheaper than standard government reports or Gallup polls.
Social data refers to data individuals create that is knowingly and voluntarily shared by them. Cost and overhead previously rendered this semi-public form of communication unfeasible, but advances in social networking technology from 2004–2010 has made broader concepts of sharing possible. The types of data users are sharing include geolocation, medical data, dating preferences, open thoughts, interesting news articles, etc.
The social data revolution enables not only new business models like the ones on Amazon.com but also provides large opportunities to improve decision-making for public policy and international development.
The analysis of large amounts of social data leads to the field of computational social science. Classic examples include the study of media content or social media content.
Every internet activity leaves behind traces of data (a digital footprint) which can be used to learn more about the user. As use of the internet is becoming more widespread, the datafication of the world is progressing rapidly: Currently, around 16 zettabytes of data are produced per year and for the year 2025 163 zettabytes of data are expected. This has led to data becoming a critical commodity. This ties together all societal actors: Public institutions, private firms, as well as individuals, each relying on data in a unique way.
Governments have been collecting data for centuries to ensure the continuance of institutional systems, through limiting the risk of defaulting credits, collecting tax based on income and providing the necessary infrastructure under consideration of their citizens' demographic distribution. In its beginnings, this data entailed written information for record keeping and control, including a census system.
This analogue process was very time- and cost-intensive, leaving little room for interpreting larger data sets. Meanwhile, corporate technological developments have moved this offline data into the digital age, allowing visualization and data analytics. In the public sphere, connecting the survey and poll methodologies with database computing, resulted in the ability to gather and store large data sets on individuals.
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Social data revolution
The social data revolution is the shift in human communication patterns towards increased personal information sharing and its related implications, made possible by the rise of social networks in the early 2000s. This phenomenon has resulted in the accumulation of unprecedented amounts of public data.
This large and frequently updated data source has been described as a new type of scientific instrument for the social sciences. Several independent researchers have used social data to "nowcast" and forecast trends such as unemployment, flu outbreaks, mood of whole populations, travel spending and political opinions in a way that is faster, more accurate and cheaper than standard government reports or Gallup polls.
Social data refers to data individuals create that is knowingly and voluntarily shared by them. Cost and overhead previously rendered this semi-public form of communication unfeasible, but advances in social networking technology from 2004–2010 has made broader concepts of sharing possible. The types of data users are sharing include geolocation, medical data, dating preferences, open thoughts, interesting news articles, etc.
The social data revolution enables not only new business models like the ones on Amazon.com but also provides large opportunities to improve decision-making for public policy and international development.
The analysis of large amounts of social data leads to the field of computational social science. Classic examples include the study of media content or social media content.
Every internet activity leaves behind traces of data (a digital footprint) which can be used to learn more about the user. As use of the internet is becoming more widespread, the datafication of the world is progressing rapidly: Currently, around 16 zettabytes of data are produced per year and for the year 2025 163 zettabytes of data are expected. This has led to data becoming a critical commodity. This ties together all societal actors: Public institutions, private firms, as well as individuals, each relying on data in a unique way.
Governments have been collecting data for centuries to ensure the continuance of institutional systems, through limiting the risk of defaulting credits, collecting tax based on income and providing the necessary infrastructure under consideration of their citizens' demographic distribution. In its beginnings, this data entailed written information for record keeping and control, including a census system.
This analogue process was very time- and cost-intensive, leaving little room for interpreting larger data sets. Meanwhile, corporate technological developments have moved this offline data into the digital age, allowing visualization and data analytics. In the public sphere, connecting the survey and poll methodologies with database computing, resulted in the ability to gather and store large data sets on individuals.