
This dataset contains 50,000 movie reviews collected from the Internet Movie Database (IMDb) platform and is intended for natural language processing (NLP), sentiment analysis, and machine learning research. Each review is labelled with a binary sentiment category: positive or negative. The dataset is structured in CSV format with the following attributes: review – textual movie review contentsentiment – sentiment label (positive or negative) The dataset can be used for: Sentiment classificationText mining and preprocessingDeep learning and NLP model trainingOpinion mining researchBenchmarking supervised learning algorithms This dataset is suitable for academic research, educational projects, and experimental studies involving machine learning, artificial intelligence, and computational linguistics.
IMDb, Sentiment Analysis, NLP, Machine Learning, Text Classification, Movie Reviews, Deep Learning, Opinion Mining, Dataset
IMDb, Sentiment Analysis, NLP, Machine Learning, Text Classification, Movie Reviews, Deep Learning, Opinion Mining, Dataset
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
