Results

Found 2 articles

Clear filters

Exploring Machine-based Idea Landscapes – The Impact of Granularity
PDF
2022 | HICSS | Citations: 0
Authors: Wahl, Julian; Stroehle, Thomas; Füller, Johann; Hutter, Katja

Abstract: Effective exploration of a landscape full of crowdsourced ideas depends on the r ... Expand

Abstract: Effective exploration of a landscape full of crowdsourced ideas depends on the right search strategy, as well as the level of granularity in the representation. To categorize similar ideas on different granularity levels modern natural language processing methods and clustering algorithms can be usefully applied. However, the value of machine-based categorizations is dependent on their comprehensibility and coherence with human similarity perceptions. We find that machine-based and human similarity allocations are more likely to converge when comparing ideas across more distant solution clusters than within closely related ones. Our exploratory study contributes to research on the navigability of idea landscapes, by pointing out the impact of granularity on the exploration of crowdsourced knowledge. For practitioners, we provide insights on how to organize the search for the best possible solutions and control the cognitive demand of searchers. Collapse

Semantic filters: exploratory study NLP method

Topics: crowdsourcing Wikipedia user-generated content programming language knowledge base

Methods: hierarchical clustering term frequency–inverse document frequency NLP method cluster analysis natural language processing
From semantics to pragmatics: where IS can lead in Natural Language Processing (NLP) research
PDF
2021 | European Journal of Information Systems | Citations: 0
Authors: Li, Yan; Thomas, Manoj a; Liu, Dapeng

Abstract: Natural Language Processing (NLP) is now widely integrated into web and mobile a ... Expand

Abstract: Natural Language Processing (NLP) is now widely integrated into web and mobile applications, enabling natural interactions between humans and computers. Although there is a large body of NLP studies published in Information Systems (IS), a comprehensive review of how NLP research is conceptualised and realised in the context of IS has not been conducted. To assess the current state of NLP research in IS, we use a variety of techniques to analyse a literature corpus comprising 356 NLP research articles published in IS journals between 2004 and 2018. Our analysis indicates the need to move from semantics to pragmatics. More importantly, our findings unpack the challenges and assumptions underlying current research trends in NLP. We argue that overcoming these challenges will require a renewed disciplinary IS focus. By proposing a roadmap of NLP research in IS, we draw attention to three NLP research perspectives and present future directions that IS researchers are uniquely positioned to address. Collapse

Semantic filters: exploratory study NLP method

Topics: database system knowledge representation social media analytics social media information retrieval

Methods: natural language processing qualitative content analysis literature study computational algorithm literature sample

Page 1 of 1

AIS11

Journals

Conferences

Semantic Filter

Found 2 articles

Exploring Machine-based Idea Landscapes – The Impact of Granularity

From semantics to pragmatics: where IS can lead in Natural Language Processing (NLP) research