How to Parse Twitter for Twitter Analysis: Part 1 | Summary and Q&A

TL;DR

Learn how to parse and extract data from Twitter using Python.

Key Insights

• 🔠 Twitter offers an API for developers, but it has limitations on the amount of data accessible.
• 🎚️ There are three official data resellers for Twitter data, each with different access levels and pricing.
• 🥡 Legal considerations should be taken into account when parsing and displaying Twitter data.

Transcript

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Questions & Answers

Q: What does the Twitter API offer for developers?

The Twitter API provides access to 1% of the full Twitter data for developers to use in their applications.

Q: Are there any official data resellers for Twitter data?

Yes, there are three official data resellers: Nip Gni, Data Sift, and Topsy, each offering different levels of access and pricing.

Q: What are the costs associated with accessing Twitter data through resellers?

Nip Gni offers access for prices starting at $500 a month, Data Sift charges 10 cents per thousand tweets, and Topsy starts at $122,000 a year.

Q: Can users legally parse and display Twitter data?

Users should be aware of the legalities surrounding parsing and displaying Twitter data, as they may not own the rights to the data they parse. It is recommended to research the legalities before using the code.

Summary & Key Takeaways

• Twitter offers an API for developers, but it only provides access to 1% of the full Twitter data.

• There are three official data resellers for Twitter: Nip Gni, Data Sift, and Topsy, each offering different levels of access and pricing.

• Legalities should be considered when using code to parse Twitter data, as users may not have the rights to display the parsed data.