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Predicting stock market using natural language processing

Puh, Karlo; Bagić Babac, Marina - In: American journal of business 38 (2023) 2, pp. 41-61

Persistent link: https://www.econbiz.de/10014342260

Exploring the effectiveness of word embedding based deep learning model for improving email classification

Asudani, Deepak Suresh; Nagwani, Naresh Kumar; Singh, … - In: Data Technologies and Applications 56 (2022) 4, pp. 483-505

Representations Transformers (BERT) pre-trained word embedding are used to identify relationships between words, which helps to … experiments compares the deep learning model performance without embedding, GloVe and BERT embedding. The experiments show that … experiment reveals that the CNN model with GloVe embedding gives slightly better accuracy than the model with BERT embedding and …

Persistent link: https://www.econbiz.de/10014712713

It’s in the News: Developing a Real Time Index for Economic Uncertainty Based on Finnish News Titles

Avela, Aleksi; Lehmus, Markku - 2020

Uncertainty may affect economic behavior of individuals and firms in a wide variety of ways, with typically negative consequences for economic growth. It is due to this fact, combined with rising political uncertainty observed lately in many countries, that uncertainty has gained increasing...

Persistent link: https://www.econbiz.de/10012603405

Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs

Foltas, Alexander - 2023

I propose a novel approach to uncover business cycle reports' priorities and relate them to economic fluctuations. To this end, I leverage quantitative business-cycle forecasts published by leading German economic research institutes since 1970 to estimate the proportions of latent topics in...

Persistent link: https://www.econbiz.de/10014317128

Developing an innovative entity extraction method for unstructured data

Zaghloul, Waleed; Trimi, Silvana - In: International Journal of Quality Innovation 3 (2017) 3, pp. 1-10

The main goal of this study is to build high-precision extractors for entities such as Person and Organization as a good initial seed that can be used for training and learning in machine-learning systems, for the same categories, other categories, and across domains, languages, and...

Persistent link: https://www.econbiz.de/10011808322

Accounting for investor sentiment in news and disclosures

Eachempati, Prajwal; Srivastava, Praveen Ranjan - In: Qualitative research in financial markets 14 (2022) 1, pp. 53-75

Persistent link: https://www.econbiz.de/10012797586

Making use of quantitative content analysis : insights from academia and business practice

Brunzel, Johannes - In: Business horizons 64 (2021) 4, pp. 453-464

Persistent link: https://www.econbiz.de/10012590329

Deciphering Indian inflationary expectations through text mining : an exploratory approach

Banerjee, Ashok; Kanodia, Ayush; Ray, Partha - In: Indian economic review : official journal of Delhi … 56 (2021) 1, pp. 49-66

Persistent link: https://www.econbiz.de/10012616831

Narrative fragmentation and the business cycle

Bertsch, Christoph; Hull, Isaiah; Zhang, Xin - In: Economics letters 201 (2021), pp. 1-6

Persistent link: https://www.econbiz.de/10012607068

Are longer reviews always more helpful? : disentangling the interplay between review length and line of argumentation

Lutz, Bernhard; Pröllochs, Nicolas; Neumann, Dirk - In: Journal of business research : JBR 144 (2022), pp. 888-901

Persistent link: https://www.econbiz.de/10013185058