🟡Please upvote the dataset if you like it.🍒

>The "IMDB Dataset of Movies Reviews and Translation" dataset has been expanded significantly and is now available on Kaggle in a modified version. Three new columns have been added to the dataset: genres, descriptions, and emotions. The original dataset only had four columns: ratings, reviews, movies, and resenhas. This extension adds to the dataset's richness and offers insightful information about movie genres, in-depth synopses, and the sentimentality of the reviews.

The addition of the Genres column provides an extensive movie classification that enables scholars and film aficionados to explore particular genres and their traits in greater detail. By examining patterns, trends, and preferences across various genres, analysts can use this data to create more specialized research and moviegoer suggestions.

The newly added Descriptions column is a valuable addition as it provides textual summaries or synopses of each movie. These descriptions offer a concise overview of the plot, characters, and themes, making it easier for users to understand and evaluate movies of interest. Researchers can leverage this information to conduct sentiment analysis, topic modeling, or recommendation systems based on movie summaries.

Finally, the Emotions column adds an intriguing dimension to the dataset. By capturing the emotional tone expressed within each description, this column allows for a deeper understanding of sentiments toward the movies. Sentiment analysis techniques can be applied to this data, enabling researchers to gain insights into emotions: like joy, anger, sadness, and more emotions associated with different movies. This information can be particularly valuable for filmmakers, production companies, marketers looking to gauge audience reactions and tailor their strategies accordingly and especially for moviegoers who like to watch movies based on emotions.

Overall, the expanded version of the "50k Movie Reviews" dataset offers a wealth of new information that fosters detailed analysis and exploration of movie genres, descriptions, and emotional responses. This dataset presents a valuable resource for researchers, data scientists, and movie enthusiasts alike, enabling a deeper understanding of the movie landscape and facilitating the development of innovative tools and applications in the field of movie analysis and recommendation systems.