Banducci, Susan
(2020).
Social media bias, trust and practices 2019.
[Data Collection]. Colchester, Essex:
UK Data Service.
10.5255/UKDA-SN-854260
The advent of Web 2.0 - the second generation of the World Wide Web, that allows users to interact, collaborate, create and share information online, in virtual communities - has radically changed the media environment, the types of content the public is exposed to as well as the exposure process itself. Individuals are faced with a wider range of options (from social and traditional media), new patterns of exposure (socially mediated and selective), and alternate modes of content production (e.g. user-generated content). In order to understand change (and stability) in opinions and behaviour, it is necessary to measure to what information a person has been exposed. The measures social scientists have traditionally used to capture information exposure usually rely on self-reports of newspaper reading and television news broadcast viewing. These measures do not take into account that individuals browse and share diverse information from social and traditional media on a wide range of platforms. According to the OECD's Global Science Forum 2013 report, social scientists' inability to anticipate the Arab Spring was partly due to a failure to understand 'the new ways in which humans communicate' via social media and the ways they are exposed to information. And social media's mixed record for predicting the results of recent UK elections suggests better tools and a unified methodology are needed to analyze and extract political meaning from this new type of data.
We argue that a new set of tools, which models exposure as a network and incorporates both social and traditional media sources, is needed in the social sciences to understand media exposure and its effects in the age of digital information. Whether one is consuming the news online or producing/consuming information on social media, the fundamental dynamic of consuming public affairs news involves formation of ties between users and media content by a variety of means (e.g. browsing, social sharing, search). Online media exposure is then a process of network formation that links sources and consumers of content via their interactions, requiring a network perspective for its proper understanding. We propose a set of scalable network-oriented tools to 1) extract, analyse, and measure media content in the age of "big media data", 2) model the linkages between consumers and producers of media content in complex information networks, and 3) understand co-development of network structures with consumer attitudes/behaviours.
In order to develop and validate these tools, we bring together an interdisciplinary and international team of researchers at the interface of social science and computer science. Expertise in network analysis, text mining, statistical methods and media analysis will be combined to test innovative methodologies in three case studies including information dynamics in the 2015 British election and opinion formation on climate change. Developing a set of sophisticated network and text analysis tools is not enough, however. We also seek to build national capacity in computational methods for the analysis of online 'big' data.
Data description (abstract)
In order to develop appropriate tools (e.g. a mobile app) we explored through a participant survey the issues such as the kinds of media coverage that engage and inform voters, whether and how this varies by subgroups such as generation, and the aspects of campaigns that contribute to more positive views of the political process. As part of ExpoNet's objectives to understand news and information exposure in the contemporary environment, we worked to to enhancing the quality of representative democracy through giving better access to citizens to quality information and the tools necessary to evaluate the news they consumed. By providing information about the nature and quality of traditional and new media election coverage over time and its impact on individuals, our research will offer pointers towards how to mobilize informed engagement with campaigns and in elections.
Data creators: |
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Sponsors: |
Economic and Social Research Council
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Grant reference: |
ES/N012283/1
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Topic classification: |
Media, communication and language
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Keywords: |
SOCIAL MEDIA, ONLINE INFORMATION, ELECTIONS, VOTING, POLITICAL CAMPAIGNS, NEWS, ACCESS TO INFORMATION, MEDIA COVERAGE
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Project title: |
Measuring Information Exposure in Dynamic and Dependent Networks (ExpoNet)
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Grant holders: |
Susan Banducci, Travis Coan, Hywel Williams, David Lazer, Lorien Jasny, Gabriel Katz
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Project dates: |
From | To |
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1 January 2016 | 28 June 2019 |
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Date published: |
05 May 2020 15:52
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Last modified: |
05 May 2020 15:52
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Collection period: |
Date from: | Date to: |
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20 May 2019 | 22 May 2019 |
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Country: |
United Kingdom |
Data collection method: |
The survey responses were collected from an online panel run by Dynata. There are 1802 respondents across a range of responses to attitudes and practices of using social media. Demographic variables have also been included. Like other companies where online samples can be purchased, Dynata uses invitations of all types including e-mail invitations, phone alerts, banners and messaging on panel community sites to include people with a diversity of motivations to take part in research. Respondents are paid for completing surveys. In terms of quality control, Dynata checks for duplicate participants by evaluating variables such as email address, matches across several demographic data, and device-related data through use of digital fingerprint technology. Participants are then directed to our survey, programmed in Qualtrics, that is hosted on a server at the University of Exeter in order to comply with data protection and privacy guidelines. |
Observation unit: |
Individual |
Kind of data: |
Numeric |
Type of data: |
Other surveys |
Resource language: |
English |
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Data sourcing, processing and preparation: |
Data were processed by the PI, checking for duplicate respondents and out of range responses.
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Rights owners: |
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Contact: |
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Notes on access: |
The Data Collection is available to any user without the requirement for registration for download/access.
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Publisher: |
UK Data Service
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Last modified: |
05 May 2020 15:52
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