Results 101 to 110 of about 34,920 (220)
Reliability measures in knowledge structure theory
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract In knowledge structure theory (KST) framework, this study evaluates the reliability of knowledge state estimation by introducing two key measures: the expected accuracy rate and the expected discrepancy. The accuracy rate quantifies the likelihood that the estimated knowledge state aligns with the true state, while the expected discrepancy ...
Debora de Chiusole +3 more
wiley +1 more source
Covid-19 Tweets Sentiment Analysis with Latent Dirichlet Allocation Topic Modeling
The Owl, 2022 Analysis of Covid-19 vaccine tweets has been an extensive focus in understanding user trends throughout the pandemic. This project concentrated on the development of a Latent Dirichlet Allocation (LDA) model along with sentiment analysis to better ...
Akhil Shiju
doaj
Decision Sciences, EarlyView.Abstract E‐commerce practitioners and researchers recognize that quality concerns are the primary drivers of customer dissatisfaction with products or services. While dissatisfaction can arise from various factors, little is known about quality and its components, specifically from the perspective of dissatisfied customers. Grounded in the foundational
Rahul Kumar +4 more
wiley +1 more source
European Management Review, EarlyView.Abstract Firm innovation and corporate social responsibility (CSR) are key strategic considerations that shape a firm's competitiveness and sustainability. However, studies exploring the relationship between the two are heterogeneous and sometimes obtain contradictory results, making it difficult to draw clear conclusions.
Daniel Alonso‐Martínez +2 more
wiley +1 more source
Extending Information Retrieval Methods to Personalized Genomic-Based Studies of Disease
Cancer Informatics, 2014 Genomic-based studies of disease now involve diverse types of data collected on large groups of patients. A major challenge facing statistical scientists is how best to combine the data, extract important features, and comprehensively characterize the ...
Shuyun Ye +2 more
doaj +1 more source
Selecting Priors for Latent Dirichlet Allocation
2018 IEEE 12th International Conference on Semantic Computing (ICSC), 2018 Latent Dirichlet Allocation (LDA) has gained much attention from researchers and is increasingly being applied to uncover underlying semantic structures from a variety of corpora. However, nearly all researchers use symmetrical Dirichlet priors, often unaware of the underlying practical implications that they bear. This research is the first to explore
Syed, Shaheen, Spruit, Marco
openaire +3 more sources
International Journal of Management Reviews, EarlyView.Abstract The present article presents an integrative review related to stewardship in all the business and management disciplines, from its initial development in 1980 to the present. Specifically, we applied a latent Dirichlet allocation‐based topic modelling analysis to almost 1200 articles, seeking to creatively synthesize the concept of stewardship
Debora Casoli +3 more
wiley +1 more source
Scalable Inference for Latent Dirichlet Allocation
, 2009 We investigate the problem of learning a topic model - the well-known Latent Dirichlet Allocation - in a distributed manner, using a cluster of C processors and dividing the corpus to be learned equally among them. We propose a simple approximated method that can be tuned, trading speed for accuracy according to the task at hand.
Petterson, James, Caetano, Tiberio
openaire +2 more sources
Conversational AI Agents: The Effect of Process and Outcome Variation on Anthropomorphism and Trust
Information Systems Journal, EarlyView.ABSTRACT Organisations increasingly deploy conversational AI agents (CAs) in agentic roles where behavioural variations are inevitable. Prior work often conflates two distinct forms of variation: outcome variation (where success fluctuates) and process variation (where the path to completion varies).
Kambiz Saffarizadeh, Mark Keil
wiley +1 more source
Narratives Contextualizing Numeric Disclosures: Insights From Earnings Calls
Journal of Business Finance &Accounting, EarlyView.ABSTRACT We investigate how narrative disclosures during earnings conference calls (ECCs) provide context for quantitative numeric disclosures in quarterly earnings releases, enhancing their informativeness. Drawing on a large sample of 34,918 quarterly ECCs from 1621 US‐listed firms from 2007 to 2020, we extract interpretable textual attributes—such ...
Imelda Taraj, Ranik Raaen Wahlstrøm
wiley +1 more source