Name: Hollywood 2025 Media Hype & Sentiment
Creator: Kaggle
License: https://opendatacommons.org/licenses/by/1-0/index.html

About this Dataset

Hollywood 2025 Media Hype & Sentiment

Dataset Overview

🎬 Tracking the "Blockbuster Battles" of December 2025

This dataset provides a real-time snapshot of the media landscape surrounding the most anticipated movie releases of late 2025. It aggregates hundreds of news headlines to quantify the "Hype Cycle" and "Critical Sentiment" for major films before they hit the box office.

Targeted Movies:

Avatar: Fire and Ash (Sci-Fi / 20th Century Studios)
Five Nights at Freddy's 2 (Horror / Blumhouse)
Sonic the Hedgehog 3 (Action / Paramount)
Nosferatu (Gothic Horror)
Mickey 17 (Sci-Fi)

Data Science Applications

NLP Sentiment Analysis: Classify news coverage as Positive (Hype) vs. Negative (Backlash).
Topic Modeling: Identify unique narrative themes for each movie (e.g., Avatar = "Visuals", FNAF = "Lore").
Trend Forecasting: Correlate news volume with "Star Power" (Director/Cast metadata).

Column Descriptors

Column	Description
`Movie_Tag`	Target label (e.g., "Avatar_Fire_and_Ash").
`Title`	Full news headline text (Primary NLP Feature).
`Source`	Publisher name (e.g., Variety, IGN).
`Publish_Date`	UTC Timestamp of publication.
`Director`	Metadata: Film director (e.g., James Cameron).
`Key_Cast`	Metadata: Lead actors (e.g., Sam Worthington).
`Description_Snippet`	Short summary of the article content.

Ethically Mined Data

Source: Public Google News RSS Feeds.
License: ODC-BY (Open Data Commons Attribution).
Update Frequency: Snapshot (Dec 10, 2025).

Acknowledgements

Image Credits Dall-E3.
Data aggregated from Google News.

Tables

Hollywood 2025 Hype Sentiment

@kaggle.kanchana1990_hollywood_2025_media_hype_and_sentiment.hollywood_2025_hype_sentiment

195.54 kB
500 rows
10 columns

CREATE TABLE hollywood_2025_hype_sentiment (
  "movie_tag" VARCHAR,
  "title" VARCHAR,
  "source" VARCHAR,
  "publish_date" TIMESTAMP,
  "director" VARCHAR,
  "key_cast" VARCHAR,
  "genre" VARCHAR,
  "studio" VARCHAR,
  "link" VARCHAR,
  "description_snippet" VARCHAR
);