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Elon Musk Article Analysis Set

Entertainment & Media Consumption

Tags and Keywords

Business

News

Text

Intermediate

Nlp

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Elon Musk Article Analysis Set Dataset on Opendatabay data marketplace

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Free

About

This dataset provides a corpus of 5,000 news articles focused on Elon Musk, a prominent business magnate and investor known for his roles at SpaceX, Tesla, The Boring Company, Neuralink, and OpenAI. The articles were gathered through web scraping from various internet sources. This collection is ideal for a range of text analysis applications, including text mining, text analytics, sentiment analysis, topic modelling, and generating word embeddings, offering valuable insights into media coverage surrounding Elon Musk and his ventures.

Columns

The dataset is structured with several informative columns for each news article:
  • article id: A unique identifier for each article.
  • title: The headline of the news article.
  • author: The name of the author who wrote the article.
  • published_date: The date and time when the article was published.
  • link: The direct URL to the full news article online.
  • clean_url: A simplified or cleaned version of the article's URL, often representing the domain.
  • excerpt: A brief summary or introductory snippet of the article content.
  • summary: A more detailed summary of the article, typically up to 250 words.
  • rights: Indicates the owner or source rights for the article content.
  • article_rank: A numerical rank based on user engagement with the article.
  • topic: The subject category of the news article, such as 'news'.
  • country: The country where the article was published or is most relevant.
  • language: The language in which the article is written.
  • authors: Additional authors associated with the article.
  • media: A link to any associated media, such as an image.
  • twitter_account: The Twitter account linked to the article's publisher.
  • article_score: A calculated score for the article.

Distribution

The dataset is provided in CSV file format and comprises 5,000 distinct news articles. Each article's information is organised into various columns, offering a structured collection of textual data. While the dataset contains 5,000 articles, there are 4,565 unique article IDs and 4,509 unique links, indicating some articles may share content or refer to similar sources.

Usage

This dataset is particularly suitable for:
  • Text mining and text analytics to extract patterns and insights from news content.
  • Sentiment analysis to gauge public and media sentiment towards Elon Musk and his companies.
  • Topic modelling to identify key themes and subjects within the news coverage.
  • Word embeddings to understand semantic relationships within the text.
  • Media studies focusing on coverage of high-profile business figures.
  • Research into current events and public discourse surrounding technology and business.

Coverage

The dataset offers a global geographic scope, encompassing news articles from various countries, including India as seen in some examples. The articles primarily cover a time range around September to October 2022, with specific publication dates noted within that period. There are no explicit notes on data availability for particular demographic groups or years outside of this general time frame.

License

CC0

Who Can Use It

This dataset is invaluable for:
  • Data scientists and machine learning engineers working on natural language processing tasks.
  • Researchers and academics in fields such as media studies, business, and social sciences.
  • Journalists and analysts seeking to understand media trends and public perception of Elon Musk.
  • Anyone interested in performing detailed textual analysis on contemporary news.

Dataset Name Suggestions

  • Elon Musk News Articles Corpus
  • Musk Media Text Data
  • Global Elon Musk News Dataset
  • Elon Musk Article Analysis Set

Attributes

Listing Stats

VIEWS

0

DOWNLOADS

0

LISTED

17/06/2025

REGION

GLOBAL

Universal Data Quality Score Logo UDQSQUALITY

5 / 5

VERSION

1.0

Free