Results 31 to 40 of about 61,609 (261)
A Topic Modelling Analysis of Living Labs Research
Technology Innovation Management Review, 2018 This study applies topic modelling analysis on a corpus of 86 publications in the Technology Innovation Management Review (TIM Review) to understand how the phenomenon of living labs has been approached in the recent innovation management literature ...
Mika Westerlund +2 more
doaj +1 more source
Continuous Semi-Supervised Nonnegative Matrix Factorization
Algorithms, 2023 Nonnegative matrix factorization can be used to automatically detect topics within a corpus in an unsupervised fashion. The technique amounts to an approximation of a nonnegative matrix as the product of two nonnegative matrices of lower rank. In certain
Michael R. Lindstrom +4 more
doaj +1 more source
An Exploratory Study of COVID-19 Information on Twitter in the Greater Region
Big Data and Cognitive Computing, 2021 The outbreak of the COVID-19 led to a burst of information in major online social networks (OSNs). Facing this constantly changing situation, OSNs have become an essential platform for people expressing opinions and seeking up-to-the-minute information ...
Ninghan Chen, Zhiqiang Zhong, Jun Pang
doaj +1 more source
MAPPING THE CHATTER: SPATIAL METAPHORS FOR DYNAMIC TOPIC MODELLING OF SOCIAL MEDIA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Topic modelling is a branch of Natural Language Processing (NLP) that deals with the discovery of conversation topics in a given document corpus. In social media, this translates into aggregating social media posts, e.g.
L. Morandini +2 more
doaj +1 more source
On a Topic Model for Sentences
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016 Probabilistic topic models are generative models that describe the content of documents by discovering the latent topics underlying them. However, the structure of the textual input, and for instance the grouping of words in coherent text spans such as sentences, contains much information which is generally lost with these models.
Georgios Balikas +2 more
openaire +2 more sources
Royal Society Open Science, 2022 This paper examines the relationship between events reported in international news via categorical discourses and Bitcoin price. Natural language processing was adopted in this study to model data-driven discourses in the crypto-economy, specifically the
Kelly Ann Coulter
doaj +1 more source
Quality of life in rural areas: A topic for the Rural Development policy?
Bulletin of Geography. Socio-Economic Series, 2014 Contemporary transformations of rural areas involve changes in land uses, economic perspectives, connectivity, livelihoods, but also in lifestyles, whereupon a traditional view of ‘the rural’ and, consequently, of ‘rural development’ no longer holds ...
Brauer René, Dymitrow Mirek
doaj +2 more sources
Topic Modelling: Going beyond Token Outputs
Big Data and Cognitive ComputingTopic modelling is a text mining technique for identifying salient themes from a number of documents. The output is commonly a set of topics consisting of isolated tokens that often co-occur in such documents.
Lowri Williams +3 more
doaj +1 more source
, 2010 We introduce supervised latent Dirichlet allocation (sLDA), a statistical model of labelled documents. The model accommodates a variety of response types. We derive an approximate maximum-likelihood procedure for parameter estimation, which relies on variational methods to handle intractable posterior expectations.
David M. Blei, Jon D. McAuliffe
openaire +3 more sources