Scraping Twitter for interest in language learning
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This purpose of this project was to determine interest in learning languages by scraping Twitter and generating visualizations with regards to Chinese, English, and Japanese. Word clouds were also generated in order to see what overlap there may be between interest in learning a language and other topics. For example, there appears to be an overlap between interest in Japanese and topics like Korean and Ariana Grande.

This type of analysis could be useful in determining where to devote resources with regards to the market for language learning. It highlights specific users that could be targeted with advertisements or @ tweets. The materials themselves could be provide increased motivation through including topics of interest to the largest number of language learners.

This could be improved by increasing the amount of data collected to include a larger time period, as overlapping topics (such as Ariana Grande) are likely influenced by the overall trending topics. Increasing the number of languages examined could be beneficial as well, as could examining interest in non-English scripts.

Work has ceased on this project.