Topic Models from GAFAM Discourse
| Name | Size | Description |
|---|---|---|
| README.txt | 14.59Kb | Readme file. |
| articles_metadata.csv | 108.0Mb | Metadata about all the documents that were used for the topic modeling analysis. |
| document_topic_matrix.csv | 293.1Mb | A file were each row corresponds to a document in the corpus that was used for the analysis, each column indicates a topic that the model determined and the cell values indicate the estimated proportion of the topic in ... |
| topic_associations.csv | 40.52Kb | This is a summary file that contains information about the topics, their role in the corpus and their associations to companies and sentiment. |
| topic_words_100.csv | 1.697Mb | A file that contains the 100 most characteristics word for each topic together with their probabilities. |
| word_topic_matrix.csv | 38.22Mb | A file that contains the topic probabilities of each word in the corpus that was used for the analysis. |
Abstract
This dataset contains the results of an LDA topic model with 200 topics that was applied to a combined corpus of newspaper articles about GAFAM (Google, Amazon, Facebook, Apple, Microsoft) companies (113 123 texts). The objective of this analysis was to analyze what discourses arise in public in relation to GAFAM companies and how the company discourse related to public media discourse about GAFAM in Europe.
For an initial summary of this model and the data that is part of this data set, seee here: https://inca-project.eu/highlights/frequency_map.php... Show more
Keyword
GAFAM; topic modeling; text analysisItem type
info:eu-repo/semantics/datasetCollections
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Except where otherwise noted, this item's license is described as info:eu-repo/semantics/openAccess