Linusrants

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linusrants is a Data & Analytics tool that provides a dataset of Linus Torvalds' rants, classified by negativity using sentiment analysis. It offers a collection of rants from 2012 to 2015, sorted by 'hate' levels.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is linusrants?

linusrants offers a unique dataset comprising Linus Torvalds' rants from the kernel mailing list, spanning from 2012 to 2015. Each rant has been classified by its negativity using sentiment analysis, providing a 'hate' score. The dataset is available in various formats including table, JSON, pickle, and TSV, with the TSV format offering extensive metadata for in-depth analysis. This resource is ideal for researchers, data scientists, and developers interested in sentiment analysis, linguistic patterns, or the communication style of prominent figures in the open-source community. Users can also build the classification system themselves using the provided Python script.

Best used for

Ideal for data scientists and developers who need to perform sentiment analysis on specific text corpora, explore linguistic patterns, and understand emotional trends in communication. Especially valuable for those interested in the historical communication of Linus Torvalds or for developing custom sentiment analysis models.

Common actions

analyze sentiment

explore datasets

classify text

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Capabilities

Key features

Sentiment-classified rants
Multiple data formats
Hate level scoring
Metadata inclusion
Python classification script

Target Audience

data scientistdeveloper

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What kind of data is included in the linusrants dataset?

The dataset includes rants from Linus Torvalds on the kernel mailing list between 2012 and 2015. Each entry contains the rant text, a 'hate' score from sentiment analysis, and metadata like permalink, date, and type (code, personal, both, unsure).

In what formats is the linusrants dataset available?

The complete list of rants is available in table form, JSON format, and pickle format. For detailed analysis and plotting, the full dataset in TSV format is recommended as it includes extensive metadata for each rant.

Can I reproduce the sentiment classification myself?

Yes, the project provides a Python script named `classify.py` that allows users to build the classification system themselves. This enables replication of the sentiment analysis process used to generate the 'hate' scores.

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