Results 131 to 140 of about 975,825 (180)

Understanding Gender-Specific Daily Care Preferences: Topic Modeling Study.

J Med Internet Res
Woo K, Min SH, Kim A, Choi S, Alexander GL, O'Malley T, Moen MD, Topaz M.   +7 more
europepmc   +1 more source

Patterns of Living Alone in South Korea Compared to Other Countries: A Public Health Perspective and YouTube Topic Modeling Analysis. [PDF]

Int J Public Health
Son H, Song S, Kim Y, Chung J.
europepmc   +1 more source

Sentiment analysis and topic modeling of social media data to explore public discourse on irritable bowel syndrome. [PDF]

Sci Rep
Shankar R, Yip AW.
europepmc   +1 more source

Autism Spectrum Disorders Discourse on Social Media Platforms: A Topic Modeling Study of Reddit Posts. [PDF]

Autism Res
Fong S, Carollo A, Vivanti G, Messinger DS, Dimitriou D, Esposito G.   +5 more
europepmc   +1 more source

Analyzing Reddit Social Media Content in the United States Related to H5N1: Sentiment and Topic Modeling Study.

J Med Internet Res
Pang O, Movahedi Nia Z, Gillies M, Leung D, Bragazzi N, Gizo I, Kong JD.   +6 more
europepmc   +1 more source

Topic modeling literary quality

, 2016
Jautze, K., van Cranenburgh, A., Koolen, C.   +2 more
openaire   +2 more sources

Public Perspectives on Palliative and Hospice Care: Social Media Content Analysis Using Topic Modeling and Multiclass Sentiment Analysis.

J Med Internet Res
Kim A, Woo K.
europepmc   +1 more source

Analysis of Breast Cancer Information on Facebook Using Neural Network-Based Topic Modeling and Metadata Analysis of English and Spanish Content: Comparative Study.

J Med Internet Res
Muralidharan R, Soto-Vasquez AD, Montenegro M, Valdez D.   +3 more
europepmc   +1 more source

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Topic Modeling

2021
Als zentrales Konstrukt der Kommunikationswissenschaft ist das Thema heute relevanter denn je. Für das Fach besitzt es als Ordnungseinheit der öffentlichen Meinung seit jeher eine besondere Bedeutung, verdankt seinen aktuellen Bedeutungszuwachs über die sozialwissenschaftliche Forschung hinaus aber erst dem Technologiewandel: Mit ihm stieg der Bedarf ...
Manika Lamba, Margam Madhusudhan
openaire   +2 more sources

Dynamic topic models

Proceedings of the 23rd international conference on Machine learning - ICML '06, 2006
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the natural parameters of the multinomial distributions that represent the topics.
Blei, David M., Lafferty, John D.
openaire   +1 more source