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Title: Consuming the Twitter Streaming API with Ruby and MongoDB Presented by: Jeff Linwood Want to build your next application off of live Twitter updates? Twitter provides a streaming API that you can filter by username, keyword, or geo-location. Using a couple of great Ruby gems, we can store tweets from the streaming API into MongoDB, a NoSQL store that's perfect for analysis. I'll go over the basics of the Twitter API, MongoDB, the mongo and tweetstream ruby gems, and how to bring it all together into a sample application. Help us caption & translate this video! http://amara.org/v/FGbv/
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The video presentation titled "Consuming the Twitter Streaming API with Ruby and MongoDB" by Jeff Linwood at the LoneStarRuby Conf 2011 addresses how to effectively utilize the Twitter Streaming API in conjunction with MongoDB through Ruby programming. The main objectives are to demonstrate how to listen for tweets based on specific criteria and to save this data for analysis. **Key Points Discussed:** - **Twitter Streaming API Overview:** The Twitter Streaming API allows developers to receive real-time tweets filtered by keywords, users, or geographic locations, enhancing data accessibility and reducing server load. - **Setup and Configuration:** Jeff begins by introducing a Ruby script that listens for tweets about Ashton Kutcher (@aplusk). The script showcases the capability to capture tweets without requiring a follow, facilitating a broader data collection. - **Data Storage with MongoDB:** MongoDB serves as a NoSQL database that complements the JSON-like structure of tweets received. Each tweet is stored as a document, facilitating further analysis. - **Streaming Process:** The Ruby TweetStream gem simplifies connection to the Twitter Streaming API and manages tweet collection asynchronously, offering an efficient way to handle real-time data. - **Limitations:** The Twitter Streaming API imposes certain restrictions, such as limits on the number of keywords and user IDs that can be tracked, and connections must be maintained to avoid excessive reconnections, which may result in account banning. - **Practical Application and Deployment:** The command-line application can be easily deployed on services like Heroku, with attention to security practices regarding credentials. - **Future Prospects:** The collected tweet data can be further analyzed for trends, sentiment analysis, or customer feedback, benefitting businesses focused on social media analytics. **Conclusion:** Lastly, the presentation reinforces the versatility and potential of integrating Twitter Streaming API with MongoDB using Ruby, encouraging viewers to explore this technology for their projects and applications in social media analytics. Jeff concludes the presentation by inviting questions about the implementation details and application usage.
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