Reddit topic and comments sentiment analyzer

This workflow analyzes and summarizes Reddit discussions about any topic of interest. Reddit has become a key channel for product reviews and discussion and is influential for decision-makers. This workflow lets you stay on top of sentiment related to your query. While it is designed for product queries, it can be used for any query type.

Tool(s) used:

Here's how it works:

It starts with adding the following inputs

1. Query (Required)

   • Description: The search term used to find relevant Reddit posts. Currently set to "abnormal security" to find discussions about the product.

   • Type: Short Text

   • Example: "abnormal security"

2. Limit (Optional)

   • Description: Controls the maximum number of Reddit posts to analyze. Default is 10, maximum allowed is 100.

   • Type: Number

   • Default: 10

   • Range: 1-100

3. Sort (Optional)

   • Description: Determines how Reddit posts should be sorted in the results.

   • Type: Short Text

   • Default: "relevance"

   • Valid options: "relevance", "hot", "top", "new", "comments"

   • Example: "relevance" returns posts most relevant to the search query

Flow steps:

1. Get subreddit topics makes a Reddit API call to fetch posts related to your query

2. Python code to get post IDs processes the API response to extract post IDs for further analysis.

3. Iterate through the posts and analyze contains two substeps:

   • An API call to get detailed post and comment data for each post ID

   • An LLM analysis step that generates a detailed content analysis report for each post, including:

     • Post metrics (upvotes, comments, etc.)

     • Overall sentiment analysis

     • Key themes and discussion points

     • Technical details about the product

     • User feedback and experiences

The workflow effectively aggregates and analyzes Reddit discussions to provide comprehensive insights about your query product reception, features, limitations, and market position. The analysis helps understand both technical aspects and user sentiment around the product.

The workflow uses Claude 3.5 Sonnet for the analysis, which is appropriate for this content analysis task. The output is in clear, consistent Markdown sections, making the findings easy to read and understand.