scholarly journals The Digital Divide Among Twitter Users and Its Implications for Social Research

2016 ◽  
Vol 35 (6) ◽  
pp. 679-697 ◽  
Author(s):  
Grant Blank

Hundreds of papers have been published using Twitter data, but few previous papers report the digital divide among Twitter users. British Twitter users are younger, wealthier, and better educated than other Internet users, who in turn are younger, wealthier, and better educated than the off-line British population. American Twitter users are also younger and wealthier than the rest of the population, but they are not better educated. Twitter users are disproportionately members of elites in both countries. Twitter users also differ from other groups in their online activities and their attitudes. These biases and differences have important implications for research based on Twitter data. The unrepresentative characteristics of Twitter users suggest that Twitter data are not suitable for research where representativeness is important, such as forecasting elections or gaining insight into attitudes, sentiments, or activities of large populations. In general, Twitter data seem to be more suitable for corporate use than for social science research.

Sociology ◽  
2017 ◽  
Vol 51 (6) ◽  
pp. 1149-1168 ◽  
Author(s):  
Matthew L Williams ◽  
Pete Burnap ◽  
Luke Sloan

New and emerging forms of data, including posts harvested from social media sites such as Twitter, have become part of the sociologist’s data diet. In particular, some researchers see an advantage in the perceived ‘public’ nature of Twitter posts, representing them in publications without seeking informed consent. While such practice may not be at odds with Twitter’s terms of service, we argue there is a need to interpret these through the lens of social science research methods that imply a more reflexive ethical approach than provided in ‘legal’ accounts of the permissible use of these data in research publications. To challenge some existing practice in Twitter-based research, this article brings to the fore: (1) views of Twitter users through analysis of online survey data; (2) the effect of context collapse and online disinhibition on the behaviours of users; and (3) the publication of identifiable sensitive classifications derived from algorithms.


Pomorstvo ◽  
2018 ◽  
Vol 32 (2) ◽  
pp. 290-296
Author(s):  
Damir Magaš ◽  
Borna Debelić ◽  
Siniša Vilke

The aim of the paper is to show a brief review of social research methods used in beach user research and coastal zone management. It is argued that this approach may effectively be used from the perspective of Integrated Coastal Zone Management (ICZM). Beaches are one of the most important factors of the sun and sea tourism, and an area where the increased users` pressure is common with the rise of tourist activity. This expansion creates increased pressure on the coastal area, the marine eco systems and, potentially, leads to a degradation of the natural environment. Social research methods provide an invaluable insight into the processes incentivizing beach users in respect to physical, social, economic and natural aspects of beach uses as well as of other parts of the coast, through the concept of the user perception. The intended result is to provide a brief methodological overview of social science research methods applied to and found in literature that can be used to be better informed of the beach management decisions as an area of ICZM interest and, in this way, contributing to the overall sustainable development of the coastal zone and increasing the competitiveness of beach tourism.


2015 ◽  
Vol 46 (3) ◽  
pp. 390-421 ◽  
Author(s):  
Tyler H. McCormick ◽  
Hedwig Lee ◽  
Nina Cesare ◽  
Ali Shojaie ◽  
Emma S. Spiro

Despite recent and growing interest in using Twitter to examine human behavior and attitudes, there is still significant room for growth regarding the ability to leverage Twitter data for social science research. In particular, gleaning demographic information about Twitter users—a key component of much social science research—remains a challenge. This article develops an accurate and reliable data processing approach for social science researchers interested in using Twitter data to examine behaviors and attitudes, as well as the demographic characteristics of the populations expressing or engaging in them. Using information gathered from Twitter users who state an intention to not vote in the 2012 presidential election, we describe and evaluate a method for processing data to retrieve demographic information reported by users that is not encoded as text (e.g., details of images) and evaluate the reliability of these techniques. We end by assessing the challenges of this data collection strategy and discussing how large-scale social media data may benefit demographic researchers.


Author(s):  
Simeon J. Yates ◽  
Jordana Blejmar

Two workshops were part of the final steps in the Economic and Social Research Council (ESRC) commissioned Ways of Being in a Digital Age project that is the basis for this Handbook. The ESRC project team coordinated one with the UK Defence Science and Technology Laboratory (ESRC-DSTL) Workshop, “The automation of future roles”; and one with the US National Science Foundation (ESRC-NSF) Workshop, “Changing work, changing lives in the new technological world.” Both workshops sought to explore the key future social science research questions arising for ever greater levels of automation, use of artificial intelligence, and the augmentation of human activity. Participants represented a wide range of disciplinary, professional, government, and nonprofit expertise. This chapter summarizes the separate and then integrated results. First, it summarizes the central social and economic context, the method and project context, and some basic definitional issues. It then identifies 11 priority areas needing further research work that emerged from the intense interactions, discussions, debates, clustering analyses, and integration activities during and after the two workshops. Throughout, it summarizes how subcategories of issues within each cluster relate to central issues (e.g., from users to global to methods) and levels of impacts (from wider social to community and organizational to individual experiences and understandings). Subsections briefly describe each of these 11 areas and their cross-cutting issues and levels. Finally, it provides a detailed Appendix of all the areas, subareas, and their specific questions.


1981 ◽  
Vol 14 (02) ◽  
pp. 262-263
Author(s):  
Thomas E. Mann

By now most of you are aware of the severe cuts in federal funding for the social and behavioral sciences and for the humanities proposed by the Reagan Administration.At the National Science Foundation, while support for the natural sciences is slated to increase, the proposed budget for the social and economic sciences calls for a 65 percent reduction.At the National Institute of Mental Health (ADAMHA), the Administration proposes toeliminateall social research, which is expected to include research on the family, socialization of children, effects of separation and divorce, evaluation of prevention efforts with children, effects of mass media on behavior of children. In addition, the definition probably will include social policy research, research on race and ethnic relations, studies of community structure and change and studies of social institutions.


1970 ◽  
Vol 18 (3) ◽  
pp. 421-456
Author(s):  
A. P. M. Coxon ◽  
Patrick Doreian ◽  
Robin Oakley ◽  
Ian B. Stephen ◽  
Bryan R. Wilson ◽  
...  

1997 ◽  
Vol 2 (3) ◽  
pp. 69-81 ◽  
Author(s):  
B. Rappert

Recent times have seen a significant reorientation in public funding for academic research across many countries. Public bodies in the UK have been at the forefront of such activities, typically justified in terms of a need to meet the challenges of international competitiveness and improve quality of life. One set of mechanisms advanced for further achieving these goals is the incorporation of users’ needs into various aspects of the research process. This paper examines some of the consequences of greater user involvement in the UK Economic and Social Research Council by drawing on both empirical evidence and more speculative argumentation. In doing so it poses some of the dilemmas for conceptualizing proper user involvement.


2020 ◽  
pp. 79-110
Author(s):  
Paul Thompson ◽  
Ken Plummer ◽  
Neli Demireva

This chapter looks at how social research gradually became organized through the work of our pioneers. It starts by looking at the growth of both universities and academic disciplines (like anthropology and sociology) as key backgrounds for understanding the growth of organized research. A major section discusses a range of early research agencies — the Colonial Research Council, Political and Economic Planning (PEP), the Institute of Community Studies, the CSO (Central Statistical Office), the SSRC, Social Science Research Council, and the UK Data Archive. Some new university-based centres are also considered: medical social science at Aberdeen, methods at Surrey and the BCCS (Birmingham Centre for Contemporary Cultural Studies). There are brief discussions of the Banbury Study with Meg Stacey and Colin Bell; and the Affluent Worker study. The chapter closes with some pioneering work on quantitative research, longitudinal studies and the rise of computing.


2020 ◽  
Vol 26 (8-9) ◽  
pp. 943-947 ◽  
Author(s):  
Marta Soler ◽  
Aitor Gómez

Social science research has been attacked by neoliberal thinkers who allege that such research lacks economic objectives. In the face of neoliberal and positivist criteria for evaluating the social impact of social science inquiry, social science researchers are developing qualitative evaluation methodologies through which we can have direct contact with citizens. These qualitative methodologies declare our social responsibility as social researchers in addressing relevant problems, especially those affecting the most vulnerable people. From these qualitative methodologies, the most vulnerable groups are included in the assessment of the social impacts of social research. Some examples of people who have participated in this qualitative evaluation include women, youth, immigrants, and Roma organizations. Participants perceived social science researchers as being far from their social reality, but in this research, they began to overcome their skepticism that social science research can help to solve those problems affecting their everyday lives.


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