Influence of social networking sites on scholarly communication: A study using literature in Artificial Intelligence

Online Social Networking Sites (SNSs) and other Artificial Intelligence (AI) systems are transforming the epistemological foundations of justice systems and influencing knowledge production concerning criminal justice and its impact. This article focuses on a dimension of criminal justice which is the impact of imprisonment on families and seeks to unravel how knowledge about this problem is produced on SNSs. To this end, it draws on a study that explored conversational networks of key stakeholders on the SNS, Twitter. Building on insights from the study, the paper unravels interdependent sociotechnical dynamics that reproduce the offline marginality of affected families and operate as barriers to equitable knowledge production. Through its analysis of the dynamics, the paper provides new insights and advances the sparse criminological scholarship on the intersections of AI systems and the delivery of justice. It specifically highlights exclusionary epistemic processes that are fomented by the infrastructure of AI systems and the social contexts in which they are deployed.

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Artificial Intelligence: A Survey on Evolution and Future Trends

Asian Journal of Applied Sciences ◽

10.24203/ajas.v9i2.6589 ◽

2021 ◽

Vol 9 (2) ◽

Author(s):

Maad M. Mijwil ◽

Rana A. Abttan

Keyword(s):

Artificial Intelligence ◽

Neural Networks ◽

Fuzzy Logic ◽

Power Systems ◽

Social Networking ◽

Social Networking Sites ◽

Future Trends ◽

Medical Field ◽

Adequate Knowledge ◽

The World

Today, the world has heard a lot about artificial intelligence (AI) and its influence in accomplishing responsibilities, and it has become famous through films, series TV and social networking sites. Artificial Intelligence (AI) is a combination of algorithms and techniques developed by developers and programmers to build metal bodies that can work for centuries with individuals. Despite the interest of everyone in this topic and its spread significantly, most people do not have adequate knowledge and understanding of this science. This science is considered as one of the essential topics in computer sciences and engineering. In this article, it has been decided to write an overview on the topic of artificial intelligence and understand how its ideas started and spread universally. In addition, there is a review of Expert Systems, Artificial Neural Networks, Fuzzy Logic, and AI applications in the medical field and power systems, especially in investigating lung images of people with COVID-19. The idea presented in this article is that the future will soon come when humans and machines will merge into cyborgs or cybernetic creatures, and they will work together when completing tasks. This idea is described as transhumanism.

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The Use of Academic Social Networking Sites in Scholarly Communication: Scoping Review

Data and Information Management ◽

10.2478/dim-2020-0050 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Milkyas Hailu ◽

Jianhua Wu

Keyword(s):

Big Data ◽

Social Networking ◽

Scoping Review ◽

Social Networking Sites ◽

Scholarly Communication ◽

Research Literature ◽

Literacy Programs ◽

User Perspective ◽

Systematic Analysis ◽

Future Studies

AbstractThis research provides a systematic analysis of 115 previous literatures on the use of academic social networking sites (ASNs) in scholarly communication. Previous research on the subject has mainly taken a disciplinary and user perspective. This research conceptualizes the use of ASNs in scholarly communication in the space between social interactions and the technologies themselves. Keyword analysis and scoping review approaches have been used to analyze the comprehensive literature in the field. The study found a geographic variation in what motivates academics to use ASNs. Scholar discovery and sharing are the primary driving factors identified in the literature. Four main themes within the research literature are proposed: motivation and uses, impact assessment, features and services, and scholarly big data. The study found that there has been an increase in scholarly big data research in recent years. The paper also discusses the key findings and concepts stated in each theme. This gives academics a better understanding of what ASNs can do and their weaknesses, and identifies gaps in the literature that are worth addressing in future investigations. We suggest that future studies may also extend the existing theoretical framework and epistemological approaches to better predict and clarify the socio-technical dimensions of ASNs use in scholarly communication. In addition, this study has implications for academic and research institutions, libraries and information literacy programs, and future studies on the topic.

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