User Data as Public Resource: Implications for Social Media Regulation

2019 ◽  
Author(s):  
Philip M. Napoli
Keyword(s):  
Social Media ◽  
Media Regulation ◽  
Public Resource ◽  
User Data

Afterword

2020 ◽  
pp. 680-683
Author(s):  
Janice L. Waldron ◽  
Stephanie Horsley ◽  
Kari K. Veblen
Keyword(s):  
Social Media ◽  
Media Use ◽  
Careful Selection ◽  
Social Media Use ◽  
Pedagogical Tools ◽  
The Future ◽  
User Data ◽  
Selection Of ◽  
Data Surface

We all feel the implications of the force of social media—for good and for ill—in our lives and in our professional world. At the time of this writing, Facebook continues with its struggle to “clean up its act” as more revelations surrounding breaches of trust and hacked user data surface in the news and various countries attempt to hold Facebook to account. Despite this, social media use continues to grow exponentially, and the potential for responsible, ethical, and transparent social media to transform the ways in which we interact with and learn from each other increase with it. As we wait to see what the future holds for social media in society, we are reminded once again that it is the careful selection of pedagogical tools such as social media, as well the guided awareness of the challenges and benefits of those tools, that remains constant, even as tools may change, disappear, or fall out of fashion.

scholarly journals Making Inferences Using Incidentally Collected Data

2016 ◽  
Author(s):  
Jonathan Mellon
Keyword(s):  
Social Media ◽  
Big Data ◽  
The Internet ◽  
User Interactions ◽  
Social Media Data ◽  
Broad Definition ◽  
User Data ◽  
The Cost ◽  
Media Data

This chapter discusses the use of large quantities of incidentallycollected data (ICD) to make inferences about politics. This type of datais sometimes referred to as “big data” but I avoid this term because of itsconflicting definitions (Monroe, 2012; Ward & Barker, 2013). ICD is datathat was created or collected primarily for a purpose other than analysis.Within this broad definition, this chapter focuses particularly on datagenerated through user interactions with websites. While ICD has beenaround for at least half a century, the Internet greatly expanded theavailability and reduced the cost of ICD. Examples of ICD include data onInternet searches, social media data, and user data from civic platforms.This chapter briefly explains some sources and uses of ICD and thendiscusses some of the potential issues of analysis and interpretation thatarise when using ICD, including the different approaches to inference thatresearchers can use.

The Use of Social Media for Urban Planning

2019 ◽  
pp. 1049-1070
Author(s):  
Fabian Neuhaus
Keyword(s):  
Social Media ◽  
Big Data ◽  
Urban Areas ◽  
Large Scale ◽  
Urban Environments ◽  
Data Systems ◽  
User Management ◽  
Social Nature ◽  
User Data ◽  
Use Of Social Media

User data created in the digital context has increasingly been of interest to analysis and spatial analysis in particular. Large scale computer user management systems such as digital ticketing and social networking are creating vast amount of data. Such data systems can contain information generated by potentially millions of individuals. This kind of data has been termed big data. The analysis of big data can in its spatial but also in a temporal and social nature be of much interest for analysis in the context of cities and urban areas. This chapter discusses this potential along with a selection of sample work and an in-depth case study. Hereby the focus is mainly on the use and employment of insight gained from social media data, especially the Twitter platform, in regards to cities and urban environments. The first part of the chapter discusses a range of examples that make use of big data and the mapping of digital social network data. The second part discusses the way the data is collected and processed. An important section is dedicated to the aspects of ethical considerations. A summary and an outlook are discussed at the end.

Taming the Internet Trolls With an Internet Ombudsperson: Ethical Social Media Regulation

2019 ◽  
Vol 12 (2) ◽  
pp. 207-224
Author(s):  
Efrat Daskal ◽  
Robert Wentrup ◽  
Dan Shefet
Keyword(s):  
Social Media ◽  
The Internet ◽  
Media Regulation

Enriching User Experience by Transforming Consumer Data Into Deeper Insights

2021 ◽  
pp. 1-18
Author(s):  
Devesh Bathla ◽  
Shraddha Awasthi ◽  
Kuber Singh
Keyword(s):  
Social Media ◽  
Life Cycle ◽  
Data Collection ◽  
User Experience ◽  
The World ◽  
User Data ◽  
Data Points ◽  
Consumer Data ◽  
Channel Interactions ◽  
Consumer Interactions

In every field, during a particular era, there is someone who stands up to a cause. There is a “North Star” in the sky to guide the “navigator” who might erringly go astray to reach the destination. The star gives direction through sheer stability. Consumer analytics as such is widely accepted throughout the world. It especially has a firm footing in enriching user experience thanks to the gigantic data collection exercise. The popularity seems to have stemmed from the fact that analytics is the real “navigator” based on data facts and the panacea for the business problems and leads the way forward whenever required. Customer journey analytics is a key instrument in the profitability framework. It also aims to provide a view of customers that is essentially dynamic in nature and other key data points observed during the life cycle of a customer. It further covers ahead of the prevailing product ownership and user data for inculcating the information such as digital channel interactions, social media, voice-of-the-consumer interactions, sentiment analysis, and more.

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