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2021 ◽  
Vol 39 (4) ◽  
pp. 369-388
Author(s):  
Bob Jansen ◽  
Glenda Browne

This paper discusses the use of wiki technology to provide a navigation structure for the online version of the Mary MacQueen Scrap Book, which contains newspaper clippings about the Victorian artist. After outlining the architecture of the wiki, the navigation structure is discussed and several questions are posed: is the navigation structure an index? If so, what type? Or is it just a linkage structure or topic map? Does such a distinction really matter? Are these definitions in reality function-based?


2021 ◽  
Vol 9 ◽  
pp. 8-46
Author(s):  
Maryja Šupa

 Social research about online crime is a multi-disciplinary field addressing a wide array of topics since its inception in the 1980s. Based on a broad review of state-of-the-art literature and gaps identified in review publications (Holt, Bossler 2014; Stratton, Powell, Cameron 2017; Maimon, Louderback 2019, and others), in this paper I outline 41 key topic in social research about online crime, classified into four broad categories: 1) research focusing on specific types of online crime, 2) research about perpetrators, victims, and law enforcement, 3) research about online crime discourses and public perceptions, 4) research putting the local and global specifics of online crime into perspective. Based on the topic map, I undertook a systematic review of literature on research about online crime published in Lithuania from the empirical social scientific perspective. The results show that very few such studies are carried out in Lithuania. From 2004 to 2020, 26 publications have been found in total. 10 of them were theoretical briefs, while 16 were based on empirical data. Out of the 41 key topic, 14 were covered in the publications, while 29 or roughly two thirds remained unaddressed. The dominant contributors were legal scholars writing about the social aspects of online crime across a variety of topics, and mostly focusing on specific crime types. The most developed topic was cyberbullying, with contributions by scholars mostly from the fields of psychology and education. To fill in these glaring gaps, it is vital to develop this field of research with an emphasis on both wider and deeper research agendas, complex, valid and reliable research data and critical theoretical approaches, inviting systematic contributions from criminology, sociology, communication and media studies, and political science.


2021 ◽  
Author(s):  
Irene Ramos-Vielba ◽  
Nicolas Robinson-Garcia ◽  
Richard Woolley

The interplay between science and society takes place through a wide range of intertwined relationships and mutual influences that shape each other and facilitate continuous knowledge flows. Stylised consequentialist perspectives on valuable knowledge moving from public science to society in linear and recursive pathways, whilst informative, cannot fully capture the broad spectrum of value creation possibilities. As an alternative we experiment with an approach that gathers together diverse science-society interconnections and reciprocal research-related knowledge processes that can generate valorisation. Our approach to value creation attempts to incorporate multiple facets, directions and dynamics in which constellations of scientific and societal actors generate value from research. The paper develops a conceptual model based on a set of nine value components derived from four key research-related knowledge processes: production, translation, communication, and utilization. The paper conducts an exploratory empirical study to investigate whether a set of archetypes can be discerned among these components that structure science-society interconnections. We explore how such archetypes vary between major scientific fields. Each archetype is overlaid on a research topic map, with our results showing that different archetypes correspond to distinctive topic areas. The paper finishes by discussing the significance and limitations of our results and the potential of both our model and our empirical approach for further research.


2021 ◽  
Vol 34 (1) ◽  
pp. 115-131
Author(s):  
Soohyun Lim ◽  
Soohyun Lim ◽  
Chanhee Park ◽  
Chanhee Park ◽  
Hyunwoo Han ◽  
...  

2021 ◽  
Vol 1 (1) ◽  
pp. 2-11
Author(s):  
Sae Dieb ◽  
Kou Amano ◽  
Kosuke Tanabe ◽  
Daitetsu Sato ◽  
Masashi Ishii ◽  
...  

2019 ◽  
Vol 19 (10) ◽  
pp. 249
Author(s):  
Pinglei Bao ◽  
Liang She ◽  
Doris Y. Tsao

2019 ◽  
Author(s):  
Alexandra Alisa Provo
Keyword(s):  

The Enhanced Networked Monographs (ENM) project was an experimental publishing project funded by The Andrew W. Mellon Foundation and carried out from 2015-2018. Over the course of the project, we developed methods to extract topics from indexes, built tools to curate the result of the integration, and created a platform for reading. This article will discuss the creation of the ENM topic map, a meta-index created by combining many individual back-of-book indexes using the Topic Curation Toolkit.


2019 ◽  
Vol 18 ◽  
pp. 7451-7469
Author(s):  
Kijung Lee

Conducting an academic research requires getting a firm grasp of ongoing research issues as well as locating research materials effectively. Often research in different fields on a similar topic can assume diverse approaches due to different objectives and research goals in their own fields. Especially in an interdisciplinary research field like cybercrime, many research topics overlap with those of other research fields. Researchers in such a field, therefore, can benefit from understanding the related domains of one’s own research.  Topic maps provide methods for understanding research domain and managing relevant information resources at the same time. In this paper, we review a topic map solution to acquire knowledge structure and to locate information resources effectively. We address current problems of cybercrime research, review previous studies that use automated methods for topic map creation, and examine existing sets of methods for automatically extracting topic map components. Especially, the methods we discuss here are text mining techniques for extracting ontology components, denoted as ontology learning.


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