scholarly journals Exploring the digital humanities research agenda: a text mining approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Soohyung Joo ◽  
Jennifer Hootman ◽  
Marie Katsurai
Keyword(s):  
Text Mining ◽  
Semantic Web ◽  
Digital Media ◽  
Digital Humanities ◽  
Topic Models ◽  
Open Data ◽  
Recent Decade ◽  
Research Trends ◽  
Large Set ◽  
Content Type

PurposeThis study aims to explore knowledge structure and research trends in the domain of digital humanities (DH) in the recent decade. The study identified prevailing topics and then, analyzed trends of such topics over time in the DH field.Design/methodology/approachResearch bibliographic data in the area of DH were collected from scholarly databases. Multiple text mining techniques were used to identify prevailing research topics and trends, such as keyword co-occurrences, bigram analysis, structural topic models and bi-term topic models.FindingsTerm-level analysis revealed that cultural heritage, geographic information, semantic web, linked data and digital media were among the most popular topics in the recent decade. Structural topic models identified that linked open data, text mining, semantic web and ontology, text digitization and social network analysis received increased attention in the DH field.Originality/valueThis study applied existent text mining techniques to understand the research domain in DH. The study collected a large set of bibliographic text, representing the area of DH from multiple academic databases and explored research trends based on structural topic models.

Exposing scholarly information as Linked Open Data: RDFizing DSpace contents

2014 ◽  
Vol 32 (6) ◽  
pp. 834-851 ◽  
Author(s):  
Nikolaos Konstantinou ◽  
Dimitrios-Emmanuel Spanos ◽  
Nikos Houssos ◽  
Nikolaos Mitrou
Keyword(s):  
Semantic Web ◽  
Design Methodology ◽  
State Of The Art ◽  
Open Data ◽  
Linked Open Data ◽  
Data Repository ◽  
Institutional Repository ◽  
Meta Data ◽  
Content Type ◽  
Compliant Approach

Purpose – This paper aims to introduce a transformation engine which can be used to convert an existing institutional repository installation into a Linked Open Data repository. Design/methodology/approach – The authors describe how the data that exist in a DSpace repository can be semantically annotated to serve as a Semantic Web (meta)data repository. Findings – The authors present a non-intrusive, standards-compliant approach that can run alongside with current practices, while incorporating state-of-the art methodologies. Originality/value – Also, they propose a set of mappings between domain vocabularies that can be (re)used towards this goal, thus offering an approach that covers both the technical and semantic aspects of the procedure.

scholarly journals Archival Linked (Open) Data: Empfehlungen für bestehende Metadaten und Massnahmen für die Zukunft am Fallbeispiel des Schweizerischen Sozialarchivs

2020 ◽  
Vol 6 (1) ◽  
pp. 312-423
Author(s):  
Fabian Würtz
Keyword(s):  
Semantic Web ◽  
Digital Humanities ◽  
Open Data ◽  
Linked Open Data ◽  
International Council ◽  
Oder Eine

Eine Kernaufgabe der Archive ist die Erschliessung des Archivguts. Bisher wurden Archivbestände meist als hierarchische und isolierte Einheiten verzeichnet. Die zunehmende Digitalisierung, neue Fachbereiche wie die Digital Humanities oder Entwicklungen wie das Semantic Web bzw. Linked Open Data haben jedoch neue Ideen in die Archivwelt getragen. Einer der deutlichsten Vorboten dieser neuen Welt ist Records in Context (RiC). Der neue Verzeichnungsstandard des wichtigen International Council on Archives (ICA) ist konzeptionell auf Linked Open Data und das Semantic Web ausgerichtet. Doch was bedeutet es für die Archive, wenn aus den bisher isolierten Beständen verlinkte und maschinenlesbare Netzwerke entstehen sollen? Wie sollen archivalische Metadaten und Datenmodelle in Linked Open Data aussehen und an welche Qualitätsansprüche sollen diese neu berücksichtigen?Um diese Fragen zu beantworten hat die Arbeit das Konzept und die Technologien die Linked Open Data zugrunde liegen vorgestellt. Danach wurden Qualitätsmerkmale für Linked Open Data zusammengetragen und der momentane Stand von Linked Open Data im Archivbereich beleuchtet. Dabei wurde unter anderem bereits existierende Ansätze und Anwendungen aus dem Archivbereich vorgestellt und mit den Qualitätsmerkmalen verglichen. Die Überprüfung der Praxistauglichkeit der Qualitätsmerkmale erfolgte am Fallbeispiel der Metadaten des Schweizerischen Sozialarchivs.Auf Basis der erarbeitenden Resultate spricht die Arbeit eine Reihe von Empfehlungen aus. Diese richten sich an Archive, die sich mit dem Thema Linked Open Data beschäftigen oder eine Anwendung in diesem Bereich planen.

Consumers experiencing vulnerability: a state of play in the literature

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aimee Riedel ◽  
Dana Messenger ◽  
David Fleischman ◽  
Rory Mulcahy
Keyword(s):  
Text Mining ◽  
Systematic Approach ◽  
Descriptive Analysis ◽  
Age Factors ◽  
Sexual Exploitation ◽  
Large Set ◽  
Subjective Experiences ◽  
Content Type ◽  
Interpretative Bias ◽  
Definition Of

Purpose The purpose of this paper is to provide a state-of-the-art review of research on consumers experiencing vulnerability to describe the current situation of the consumers experiencing vulnerability literature and develop an up-to-date synthesised definition of consumers experiencing vulnerability. Design/methodology/approach This systematic review, guided by the PRISMA framework, takes a multi-disciplinary approach to identify 310 articles published between 2010 and 2019 examining consumers experiencing vulnerability. Descriptive analysis of the data is undertaken in combination with a thematic and text mining approach using Leximancer software. Findings A definition of consumers experiencing vulnerability is developed- “unique and subjective experiences where characteristics such as states, conditions and/or external factors lead to a consumer experiencing a sense of powerlessness in consumption settings”. The findings reveal consumers experiencing vulnerability have often been classified using a uni-dimensional approach (opposed to a multi-dimensional), focussing on one factor of vulnerability, the most prevalent of these being economic and age factors. A lack of research has examined consumers experiencing vulnerability based upon geographical remoteness, gender and sexual exploitation. Originality/value This paper is one of the first to examine consumers experiencing vulnerability using a systematic approach and text mining analysis to synthesise a large set of articles, which subsequently reduces the potential for researchers’ interpretative bias. Further, it is the first to generate a data-driven definition of consumers experiencing vulnerability. It provides targeted recommendations to allow further scholarly, policy and practical contributions to this area.

Research trends analysis using text mining in construction management: 2000–2020

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Eymen Çağatay Bilge ◽  
Hakan Yaman
Keyword(s):  
Text Mining ◽  
Information Management ◽  
Bibliometric Analysis ◽  
Construction Management ◽  
Detection Method ◽  
Research Trends ◽  
Information Modeling ◽  
Topic Detection ◽  
Content Type ◽  
Building Information

PurposeThis study aims to identify the trends that have changed in the field of construction management over the last 20 years.Design/methodology/approachIn this study, 3,335 journal articles published in the years 2000–2020 were collected from the Web of Science database in construction management. The authors applied bibliometric analysis first and then detected topics with the latent Dirichlet allocation (LDA) topic detection method.FindingsIn this context, 20 clusters from cluster analysis were found and the topics were extracted in clusters with the LDA topic detection method. The results show “building information modeling” and “information management” are the most studied subjects, even though they have emerged in the last 15 years “building information modeling,” “information management,” “scheduling and cost optimization,” “lean construction,” “agile approach” and “megaprojects” are the trend topics in the construction management literature.Research limitations/implicationsThis study uses bibliometric analysis. The authors accept that the co-citation and co-authorship relationship in the data is ethical. They accept that honorary authorship, self-citation or honorary citation do not change the pattern of the construction management research domain.Originality/valueThere has been no study conducted in the last 20 years to examine research trends in construction management. Although bibliometric analysis, systematic literature reviews and text mining methods are used separately as a methodology for extracting research trends, no study has used enhanced bibliometric analysis and the LDA topic detection text mining method.

scholarly journals Business model analytics: technically review business model research domain

foresight ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 654-679 ◽  
Author(s):  
Nastaran Hajiheydari ◽  
Mojtaba Talafidaryani ◽  
SeyedHossein Khabiri ◽  
Masoud Salehi
Keyword(s):  
Text Mining ◽  
Business Model ◽  
Research Trends ◽  
Intellectual Structure ◽  
Field Of Study ◽  
Research Issues ◽  
Content Type ◽  
Main Research ◽  
Model Field ◽  
Timeline Analysis

Purpose Although the business model field of study has been a focus of attention for both researchers and practitioners within the past two decades, it still suffers from concern about its identity. Accordingly, this paper aims to clarify the intellectual structure of business model through identifying the research clusters and their sub-clusters, the prominent relations and the dominant research trends. Design/methodology/approach This paper uses some common text mining methods including co-word analysis, burst analysis, timeline analysis and topic modeling to analyze and mine the title, abstract and keywords of 14,081 research documents related to the domain of business model. Findings The results revealed that the business model field of study consists of three main research areas including electronic business model, business model innovation and sustainable business model, each of which has some sub-areas and has been more evident in some particular industries. Additionally, from the time perspective, research issues in the domain of sustainable development are considered as the hot and emerging topics in this field. In addition, the results confirmed that information technology has been one of the most important drivers, influencing the appearance of different study topics in the various periods. Originality/value The contribution of this study is to quantitatively uncover the dominant knowledge structure and prominent research trends in the business model field of study, considering a broad range of scholarly publications and using some promising and reliable text mining techniques.

Open data?

2014 ◽  
Vol 24 (2) ◽  
pp. 163-180 ◽  
Author(s):  
Erik Borglund ◽  
Tove Engvall
Keyword(s):  
Mixed Method ◽  
Text Analysis ◽  
Design Methodology ◽  
Open Data ◽  
Large Set ◽  
Word Count ◽  
Content Type ◽  
Archival Practice ◽  
Quantitative Text Analysis ◽  
Method Approach

Purpose – The aim of the article is to investigate what characterizes the information constructs that the archival discourse and the open data discourse communicate in text, and what their similarities and differences are. This article proposes that it is possible to see the open data initiative and modern archival practice as two discourses that have used different terminology to express and communicate their messages in the literature. In this article, we have applied a hypothesis-like assumption that the information constructs used in open data are actually nothing other than records, as they are in the archival discourse. Design/methodology/approach – This article is based on a mixed method approach. A quantitative text analysis (word count) was carried out in a large set of documents representing the open data discourse and in the archival discourse. This was followed by a qualitative text analysis. Findings – It was found that both discourses did focus on records. However, the opendata discourse very seldom used the term record, but used information and data much more frequently. The archival discourse used the term information almost as often as record. A possible adaption of communication strategies can be identified, targeting a much wider audience through a user-centered approach. This could be an indication of a change in the archival discourse, which seems to be moving from a discourse that is very much regulated by law toward a discourse that is more focused on benefit and usability. Originality/value – This research indicates that it is possible to interpret both the open data and the archival discourse as one united discourse, an effect derived from working with e-government. There is an ongoing harmonization of the words used, and in the studied archival discourse, a more user- and business-oriented focus can be seen.

Pedagogy and public-funded research: an exploratory study of skills in digital humanities projects

2019 ◽  
Vol 75 (3) ◽  
pp. 550-576 ◽  
Author(s):  
Deborah A. Garwood ◽  
Alex H. Poole
Keyword(s):  
Digital Humanities ◽  
Academic Research ◽  
Open Data ◽  
Project Based Learning ◽  
Project Work ◽  
Structured Interviews ◽  
Problem Solving Skills ◽  
Content Type ◽  
Funded Research ◽  
Analytical Skills

Purpose Public-funded research in digital humanities (DH) enhances institutional and individual research missions and contributes open data to a growing base of globally networked knowledge. The Digging into Data 3 challenge (DID3) (2014–2016) is an international, interdisciplinary and collaborative grant initiative, and the purpose of this paper is to explore skills that faculty and students brought to projects and others they acquired and shared on collaborative teams. Design/methodology/approach Rooted in the naturalistic paradigm, this qualitative case study centers on semi-structured interviews with 53 participants on 11 of the 14 DID3 projects. Documentary evidence complements empirical evidence; analysis is constructivist and grounded. Findings Hailing from diverse academic research institutions, centers and repositories, participants brought 20 types of discipline-based or interdisciplinary expertise to DID3 projects. But they reported acquiring or refining 27 other skills during their project work. While most are data-related, complementary programming, management and analytical skills push disciplinary expertise toward new frontiers. Project-based learning and pedagogy function symbiotically; participants therefore advocate for aligning problem-solving skills with pedagogical objectives at home institutions to prepare for public-funded DH projects. A modified content analysis juxtaposes DID3 skills with those advanced in 23 recent DH syllabi to identify commonalities and gaps. Originality/value Pedagogy has an important yet under-researched and underdeveloped role in public-funded DH research.

A bibliometric review of advances in building information modeling (BIM) research

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ayotunde Babalola ◽  
Shamsudeen Musa ◽  
Mariam Temisola Akinlolu ◽  
Theo C. Haupt
Keyword(s):  
Text Mining ◽  
Bibliometric Analysis ◽  
Information Exchange ◽  
Laser Scanning ◽  
Building Information Modeling ◽  
Research Trends ◽  
Information Modeling ◽  
Historical Building ◽  
Content Type ◽  
Building Information

Purpose This paper aims to provide a bibliometric analysis of advances in building information modeling (BIM) research globally. It provides a recent state-of-the-art assessment on trends as it relates to the architecture, engineering and construction (AEC) industry. Being a vastly emerging research area, there is a need for the appraisal of research trends. Design/methodology/approach A comprehensive bibliometric analysis was conducted using a dual step filtering system on an initial volume of 2347 documents in the first stage between 2010 and 2020, and of 311 publications in the final stage of the analyses which emphasized more on 2015–2020 from the WoS database. Frequency analyses on the sources, affiliations, authors and country/ region of publication were assessed in the first stage of the analyses. Co-authorship and evidence of author collaboration were also examined. The second stage included a co-occurrence keyword network analysis. Further, text mining/mapping of the abstract of the documents was performed. Findings Emerging trends in the field of BIM research include but are not limited to historical building information modeling (h-BIM) applications, the use of blockchain technology, digital twin, Construction Operations Building information exchange (COBiE), Industry Foundation Classes (IFC), dynamo-bim, energy plus software and BIM laser scanning innovations. The possibility of these innovations solving some current BIM challenges were also discussed. Originality/value The study provides an insight into the BIM research trends globally while identifying existing challenges. The study uses text mining of unstructured abstracts, which has not been reported in BIM research.

scholarly journals Making sense of customer service experiences: a text mining review

2019 ◽  
Vol 33 (1) ◽  
pp. 88-103 ◽  
Author(s):  
Dominik Mahr ◽  
Susan Stead ◽  
Gaby Odekerken-Schröder
Keyword(s):  
Text Mining ◽  
Customer Service ◽  
Outcome Measures ◽  
Service Providers ◽  
Marketing Research ◽  
Future Research ◽  
Large Set ◽  
Sensory Stimuli ◽  
Content Type ◽  
Five Dimensions

Purpose The purpose of this paper is to systematically review the concepts and theories underlying customer service experience (CSE) and its underlying five dimensions (physical, social, cognitive, affective and sensorial). In this research, the contribution of the sensorial dimension to CSE research is emphasized. Senses are especially important in forming perceptions within servicescapes that are typically rich in sensory stimuli. Design/methodology/approach This study systematically identifies 258 articles published between 1994 and 2018 in services and marketing journals. The analysis uses a text mining approach with the Leximancer software to extract research concepts and their relationships. Findings The results demonstrate a shift from CSE research focused on brands and products toward value and interaction, around three focal areas: service system architecture, with its value creation processes; servicescape, with an increasingly digital interaction interface and outcome measures, with a stronger focus on emotional and relational metrics. In CSE research, the physical, social and cognitive dimensions are mostly researched in the focal areas of servicescape and outcome measures. Although important in practice, the sensorial dimension is the least investigated CSE dimension in service marketing research. Text mining insights demonstrate rich opportunities for sensorial research, particularly in studies on servicescape. Practical implications The synthesis will inform managers and service providers which elements of CSE are most relevant to customers when forming perceptions. These insights help service providers to control, manage and design (multi)-sensory stimuli that influence how customers will make sense of the servicescape. Originality/value This research is one of the first studies to examine the conceptual structure of CSE with a text mining approach that systematically analyzes a large set of articles, therein reducing the potential for researchers’ interpretative bias. The paper provides an assessment of the role of the largely neglected but crucial sensorial dimension, and offers future research suggestions into this emerging topic.

Offen, kreativ und kollaborativ, dazu noch kritisch? : Zwei koreanische Beispiele von ,Digital Humanities‘

2020 ◽  
Vol 52 (1) ◽  
pp. 91-98
Author(s):  
Von Yun-Young Choi
Keyword(s):  
Data Mining ◽  
Information System ◽  
Big Data ◽  
Geographic Information System ◽  
Text Mining ◽  
Digital Humanities ◽  
Open Data ◽  
Geographic Information ◽  
Linked Open Data

Unter dem Begriff ,Digital Humanities‘ versteht man die Erforschung und Ausbildung der Geisteswissenschaften und das damit verbundene neuartige Schaffen von Texten mithilfe neuester Informationstechnologien.1 Digital Humanities umfassen nicht nur digitale Arbeitsinstrumente, sondern auch deren stellvertretende Bereiche, Datenbanken, Linked Open Data (LOD), Geographic Information System (GIS), Informationsvisualisierung oder Ontologie, Big Data oder Data Mining, Text Mining oder elektronische Kulturatlanten, sowie deren Didaktik. Der Begriff ,Digital Humanities‘ umfasst nicht nur die Digitalisierung von Texten, sondern auch die Verwendung der digitalen Technologien innerhalb der Geisteswissenschaften und weithin die Reflexion über die Technologie selbst. Wenn man von Digital Humanities spricht, stellt man sich oft digitale Datenbanken vor. Den Anfang machte der Index Thomisticus, eine Lemmatisierung sämtlicher Texte von Sankt Aquinas, die von Priester Roberto Busa (1913–2011) in Italien entwickelt wurde.2 Dieser Vorreiter der Digital Humanities hatte bereits im Jahre 1946 mit IBM eine großangelegte Datenbank geplant. Der Aufbau der Texte in 56 Bänden dauerte ca. 30 Jahre. 1989 wurden die Ergebnisse in CD-Form und ab 2004 im Internet (Corpus Thomisticum) veröffentlicht.3 Wie man an diesem Beispiel sieht, gewinnt man durch die Digitalisierung von Texten neue und breitere Verfügungs- und Verarbeitungskapazitäten. Man kann maschinell lesbare Texte speichern und diese auch auf und für verschiedene Weisen nutzbar machen, z. B. anhand von Suchmaschinen, Stichwortsuchen oder Häufigkeitsuntersuchungen.

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