Metadata-Version: 2.1
Name: keyword_explorer
Version: 0.5a0
Summary: A set of tools for producing and exploring keywords on Twitter and the Wikipedia
Home-page: https://github.com/pgfeldman/KeywordExplorer
Author: Philip Feldman
Author-email: phil@philfeldman.com
License: MIT
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
License-File: LICENSE

Explorer Apps
====================================
There are six applications in this project: KeywordExplorer, TweetsCountExplorer, TweetDownloader, WikiPageviewExplorer, TweetEmbedExplorer, and ModelExplorer. They, and the classes that support them, can be installed with pip:

    pip install keyword-explorer

**KeywordExplorer** is a Python desktop app that lets you use the GPT-3 to search for keywords and Twitter to see if those keywords are any good.

**TweetCountsExplorer** is a Python desktop app that lets you explore the quantity of tweets containing keywords over days, weeks or months.

**TweetDownloader** is a Python desktop app that lets you select and download tweets containing keywords into a database. The number of Tweets can be adjusted so that they are the same for each day or proportional. Users can apply daily and overall limits for each keyword corpora.

**WikiPageviewExplorer**  is a Python desktop app that lets you explore keywords that appear as articles in the Wikipedia, and chart their relative page views.

**TweetEmbedExplorer** is a Python desktop app for analyzing, filtering, and augmenting tweet information. Augmented information can them be used to create a train/test corpus for finetuning language models such as the GPT-2.

**ModelExplorer** is a Python desktop app that lets a user interact with a finetuned GPT-2 model trained using EmbeddingExplorer

Full documentation is available at https://github.com/pgfeldman/KeywordExplorer#readme
