Explore Twitter Trends Both Twitter and its trends have ingrained themselves into every aspect of our life. Popular hashtags used on Twitter are referred to as "Twitter trends," and they are organized by geography. Twitter uses the Yahoo Where On Earth ID to track trends in each important location. When you visit Twitter.com, the global trends appear on the left, and you may use the trends to see the top 50 trends for any location. Insert an API object. In this post, we'll switch to the notebook to retrieve location-specific trends and use a package for JSON data format to display the response we get from Twitter. Then, using this information, we will construct Python sets over which we can perform intersection operations. Retrieving Twitter Trends Firstly, let us get the Yahoo Where On Earth ID for each location. The world has the ID number one, and you can look it up online for your location using the link provided. Once you have the ID, we can use the trends.place from the Twitter API to get the top 50 trends for any location. Here, we give you the San Diego lookup as an example. Using the Twitter API object we created, Twitter_API, we can retrieve trends for a particular place. The response we receive from Twitter is in JSON format, which is a semi-structured data format used to pass information in internet applications. It is similar to nested Python dictionaries and lists. Working with JSON Once Twitter has responded, we may manipulate the data using Python's JSON package. Let's use the dumps function to provide a more legible version of the output after importing the JSON module. Next, we can create Python sets from the data to run intersection operations over. Intersection operations are used to find the common elements between sets. In this case, we can use intersection operations to find the common trends between locations. Conclusion In conclusion, keeping up with trending topics and conversations on Twitter is a great idea. We can extract area-specific trends using the Twitter API since Twitter groups trends according to location. We can work with the data and execute intersection operations to look for consistent patterns across places using JSON and Python sets. Overall, this article has covered the basics of retrieving and working with Twitter trends data. With this information, you can start exploring the trends in your location and beyond.