The Performative and Interpretive Labour of Videoconferencing: Findings from a Literature Review on 'Zoom' Fatigue

2022 | International Conference on Information Systems | Citations: 0

Authors: Wang, Blair; Prester, Julian

Abstract: Videoconferencing fatigue or 'Zoom' fatigue has emerged as a distinct and press ... Expand

Abstract: Videoconferencing fatigue or 'Zoom' fatigue has emerged as a distinct and pressing phenomenon in light of rapid videoconferencing adoption during and after the COVID-19 pandemic. As part of an ongoing broader literature review project, we find that extant literature primarily conceptualises videoconferencing fatigue as an error that needs to be detected and corrected based on techniques derived from medical, psychological, technological and media theories. However, we observe that videoconferencing is also a work activity, and thus consider what additional insights on videoconferencing fatigue could be obtained by deconstructing videoconferencing according to the labour that is involved in videoconferencing. Based on thematic analysis of the extant literature, we thus develop a perspective on videoconferencing in relation to the performative and interpretive labour that videoconferencing entails. This new way of thinking about videoconferencing fatigue, as labour cost, enables us to offer implications for theory and practice, and comment on directions for future research. Collapse

Topics: video conference pandemic database system organization structure electronic mail

Methods: literature study literature sample qualitative content analysis structured literature research synthesis

Theories: media theory

Combining Graph Exploration and Fragmentation for Scalable RDF Query Processing

2021 | Information Systems Frontiers | Citations: 0

Authors: Khelil, Abdallah; Mesmoudi, Amin; Galicia, Jorge; Bellatreche, Ladjel; Hacid, Mohand-Saïd; Coquery, Emmanuel

Abstract: The flexibility offered by the Resource Description Framework (RDF) has led it t ... Expand

Abstract: The flexibility offered by the Resource Description Framework (RDF) has led it to become a very popular standard for representing data with an undefined or variable schema using the concept of triples. Its success has resulted in many large scale multidisciplinary datasets, that have prompted the development of efficient RDF processing systems. Current approaches can be distinguished into two groups: the first, adopting the relational model storing the triples in tables, and the second creating data structures that model RDF data as a graph. The strategies of the first group are more easily scalable since they apply optimization strategies from the relational model like indexing and fragmentation. However, these approaches suffer many overheads when dealing with complex queries (e.g. compounded SPARQL graphs involving filters) persistent in existing applications. On the other hand, graph-based systems that use more complex data structures fail to efficiently manage the main memory and are not scalable in computer hardware with limited resources. In this paper, we propose a novel approach to perform queries (Basic Graph Patterns, Wildcards, Aggregations and Sorting) on RDF data. We propose to combine both RDF graph exploration with physical fragmentation of triples. In this work, we describe our graph-based storage and query evaluation models. Then, we detail the architecture of our system and we largely explain the strategy, based in the Volcano execution model, used to manage the main memory at query runtime. We conducted extensive experiments on synthetic and real datasets to evaluate the efficiency of our proposal. We compared our performance with a relational-based (Virtuoso), a graph-based (gStore) and an intensive-indexing (RDF-3X) approach. According to our evaluation, our system offers the best compromise between efficient query processing and scalability. Collapse

Topics: computer hardware Neo4j graph database structured query language database system

Methods: experiment computational algorithm leading question literature study

A personalized paper recommendation method considering diverse user preferences

2021 | Decision Support Systems | Citations: 2

Authors: Li, Yi; Wang, Ronghui; Nan, Guofang; Li, Dahui; Li, Minqiang

Abstract: Prior studies of paper recommendation methods that consider historical user pref ... Expand

Abstract: Prior studies of paper recommendation methods that consider historical user preferences rarely adequately address the complexity of user preferences and interests. We propose a method to recommend personalized papers based on a heterogeneous network that includes papers, venues, authors, terms, and users as well as the relations among these entities. We investigate meta-paths in the network to capture user preferences and apply random walks on these meta-paths to measure recommendation scores of candidate papers to target users. We employ a personalized weight learning process to discover a user’s personalized weights on different meta-paths using Bayesian Personalized Ranking as the objective function. A global recommendation score is calculated by combining recommendation scores on different meta-paths with personalized weights. We conducted experi­ ments using two different datasets and the results showed that the proposed method performed better than other baseline methods. Collapse

Topics: recommender system social network location based service

Methods: experiment machine learning literature sample co-citation analysis term frequency–inverse document frequency

Link prediction in heterogeneous information networks: An improved deep graph convolution approach

2021 | Decision Support Systems | Citations: 2

Authors: Wang, Xi; Chai, Yibo; Li, Hui; Wu, Danqin

Abstract: Heterogeneous information networks (HINs) refer to logical networks involving en ... Expand

Abstract: Heterogeneous information networks (HINs) refer to logical networks involving entities of multiple types and their multiple relations, which are widely used for modeling real-world systems with rich features and intricate patterns. Link prediction in such networks is a consistent interesting research question due to its methodological and practical implications in the business field. This study develops an improved spatial graph convolution network to learn predictive vertex embeddings with minimal information loss based on local community dis­ covery and to handle the complexity of link predictions in the context of HINs. An optimizable kernel layer is designed to measure the similarity of pairwise vertex embeddings. The effectiveness of the proposed method is validated using four real-world HINs: WordNet, MovieLens, DBLP, and Douban. The results of the experiments demonstrate that the proposed method outperforms several benchmark algorithms, achieving F1-scores of 87.65%, 84.27%, 82.99%, and 89.96% on the four HINs, respectively. The findings of this study can inform the design and improvement of related information systems. Collapse

Topics: knowledge representation ebook

Methods: computational algorithm machine learning support vector machine deep learning WordNet

Time-based Gap Analysis of Cybersecurity Trends in Academic and Digital Media

2020 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Alagheband, Mahdi R.; Mashatan, Atefeh; Zihayat, Morteza

Abstract: This study analyzes cybersecurity trends and proposes a conceptual framework to ... Expand

Abstract: This study analyzes cybersecurity trends and proposes a conceptual framework to identify cybersecurity topics of social interest and emerging topics that need to be addressed by researchers in the field. The insights drawn from this framework allow for a more proactive approach to identifying cybersecurity patterns and emerging threats that will ultimately improve the collective cybersecurity posture of the modern society. To achieve this, cybersecurity-oriented content in both media and academic corpora, disseminated between 2008 and 2018, were morphologically analyzed via text mining. A total of 3,556 academic papers obtained from the top-10 highly reputable cybersecurity academic conferences, and 4,163 news articles collected from the New York Times were processed. The LDA topic modeling followed optimal perplexity and coherence scores resulted in 12 trendy topics. Next, the time-based gap between these trendy topics was analyzed to measure the correlation between media and trendy academic topics. Both convergences and divergences between the two cybersecurity corpora were identified, suggesting a strong time-based correlation between these resources. This framework demonstrates the effective use of automated techniques to provide insights about cybersecurity topics of social interest and emerging trends and informs the direction of future academic research in this field. Collapse

Topics: IT security malware privacy social network mobile application

Methods: topic model survey experiment term frequency–inverse document frequency Gensim

Selecting Conference Venues: A Carbon Footprint Calculator Based on Past Editions

2020 | European Conference On Information Systems | Citations: 0

Authors: Diaz, Oscar; Contell, Jeremias P.

Abstract: Conferences are an integral part of academic life. Yet, this practice is increa ... Expand

Abstract: Conferences are an integral part of academic life. Yet, this practice is increasingly questioned due to the large carbon footprint that attendee flying involves. On an individual basis, carbon footprint calculators have become a widely used intervention to act upon individual practice by increasing the provision of information. Likewise, we aim at acting upon Conference Committees by making them aware of the carbon penalty associated with their events. Informed by the theory of planned behaviour, we introduce a purposeful artefact: "carbon layers". The name aims at conveying "the what" (i.e. carbon calculation) as well as "the how" (i.e. the carbon footprint is layered on top of the conference's Web-embodiment). Architecturally, these artefacts are realized as browser extensions on top of the conference's embodiment, let this be the conference's website or a bibliography website. This vision is realized through grnDBLP, a Carbon Layer for the DBLP website. By installing such extension, committees can become aware of the carbon footprint estimates for their previous conference editions, and the footprint for potential venues calculated by extrapolation. A pilot survey is conducted, with a view to spark further debate on how to increase the sustainability of scientific conferences. Collapse

Topics: website electronic commerce web page societal context electronic mail

Methods: design principle pilot survey design artifact kernel theory experiment

Theories: theory of planned behavior

A Bibliometric Analysis of the HICSS Software Technology Track

2020 | HICSS | Citations: 0

Authors: Grønli, Tor-Morten; Majchrzak, Tim A; Kaindl, Hermann; Wien, TU

Abstract: The HICSS Software Technology track has a long tradition and many papers have be ... Expand

Abstract: The HICSS Software Technology track has a long tradition and many papers have been published as part of its history. Its impact in terms of citations, paper contributions, author share and community impact does not yet seem to have been investigated, though. In particular, software technology has evolved, and as it stands, it is of primary importance for mobile computing, the Internet-of-Things and Cyber-physical Systems. Hence, the development of these topics and the related impact of this track are of particular interest. In this paper, we present a bibliographic analysis as a first step towards such an investigation. We found that the history of the track is indeed noteworthy. Our results include finding a few extremely much cited papers, some curious tendencies, and a generally favourable outlook for HICSS. We found that indeed many papers in the history of this HICSS track addressed mobile technology and are highly cited. Together with providing insight into track, paper and author impact, we also raise questions worth of further investigation to understand the role of the HICSS Software Technology track and its impact on the academic field and society. Collapse

Topics: mobile system internet of things systems development spreadsheet Visual Basic

Methods: bibliometric analysis descriptive statistic co-citation analysis literature study

DPRel: A Meta-Path Based Relevance Measure for Mining Heterogeneous Networks

2019 | Information Systems Frontiers | Citations: 0

Authors: Gupta, Mukul; Kumar, Pradeep; Bhasker, Bharat

Abstract: Mining a heterogeneous network requires measuring the relatedness between object ... Expand

Abstract: Mining a heterogeneous network requires measuring the relatedness between objects represented as nodes in the network. Relevance measurement on objects in a heterogeneous network is a challenging problem. Many researchers transform a heterogeneous network into the corresponding homogeneous network and then apply conventional similarity measures. However, this approach involves information loss as various path semantics are lost in the transformation process. In this paper, we study the problem of relevance measurement on objects in a heterogeneous network and propose a meta-path based semi-metric measure for relevance measurement on objects in a general heterogeneous network with a specified network schema. The proposed measure incorporates path semantics by following the specified meta-path. For measuring relatedness between objects using the proposed measure, the heterogeneous network is converted into a bipartite network consisting of source and target type objects following the specified meta-path. To validate the effectiveness of the proposed measure, we compare its performance with the existing meta-path based semi-metric measures applicable to heterogeneous networks. Experiments are performed on real-world datasets to show the effectiveness of the proposed measure. Collapse

Topics: information retrieval

Methods: cluster analysis experiment machine learning computational algorithm literature study

The rise of motivational information systems: A review of gamification research

2019 | International Journal of Information Management | Citations: 232

Authors: Koivisto, Jonna; Hamari, Juho

Abstract: Today, our reality and lives are increasingly game-like, not only because games ... Expand

Abstract: Today, our reality and lives are increasingly game-like, not only because games have become a pervasive part of our lives, but also because activities, systems and services are increasingly gamified. Gamification refers to designing information systems to afford similar experiences and motivations as games do, and consequently, attempting to affect user behavior. In recent years, popularity of gamification has skyrocketed and manifested in growing numbers of gamified applications, as well as a rapidly increasing amount of research. However, this vein of research has mainly advanced without an agenda, theoretical guidance or a clear picture of the field. Collapse

Topics: gamification database system affordance social network crowdsourcing

Methods: experiment literature study literature sample mixed method theory development

Theories: theory of affordance

LEARNING CONCEPTUAL MODELING: STRUCTURING OVERVIEW, RESEARCH THEMES AND PATHS FOR FUTURE RESEARCH

2019 | European Conference On Information Systems | Citations: 0

Authors: Rosenthal, Kristina; Ternes, Benjamin; Strecker, Stefan

Abstract: Conceptual modeling marks an essential expertise for understanding and shaping t ... Expand

Abstract: Conceptual modeling marks an essential expertise for understanding and shaping the digital enterprise. Research on learning and, correspondingly, teaching conceptual modeling forms a diverse body of knowledge involving foci on various learning theories and approaches, learning outcomes and barriers. This review of literature on learning and teaching conceptual modeling identifies prevalent and emerging research themes, and presents a structuring overview of contributions to the field. Based on a systematic and purposeful sampling of publications combining different search strategies, we compile and analyze 121 contributions published between 1986 and 2017 to initiate further discussion on framing the learning and teaching of conceptual modeling in the light of learning paradigms. Future research can draw upon the identified research themes and gaps to advance our knowledge on learning conceptual modeling. Collapse

Topics: database system system support systems development

Methods: conceptual modelling design science literature study qualitative coding data modeling