How to classify Reddit Community Channels with generative AI

Text Classification

If you’re a marketer, community manager, or data analyst, you understand the importance of monitoring and engaging with online communities. Reddit is one of the most popular social media platforms where users share and discuss content on various topics through subreddits. This post will show you how to classify Reddit community channels using generative AI, giving you a better understanding of your audience and how to tailor your content strategy to their interests.

What is Text Classification?

Text classification is a natural language processing (NLP) technique that involves using machine learning algorithms to automatically assign one or more predefined categories or labels to a given piece of text. In the case of Reddit community channels, we will use text classification to identify the topic or theme of each subreddit. This will help us to better understand the interests of our target audience and tailor our content strategy to their needs.

Example Use Cases

Use cases for classifying Reddit community channels include:

Identify the most popular topics on the platform
Find subreddits relevant to your product or service
Identify potential partners or influencers in your niche
Monitor trends and sentiment around a particular topic
Discover new content ideas for your marketing strategy

Teams that might find these use cases helpful include: marketing, community management, social media, and data analytics.

Finding your input data and categories

First, you need to identify the data that you want to work with. In this case, we will be using the Reddit API to extract a list of subreddits and their corresponding descriptions. You can access the Reddit API here: https://www.reddit.com/dev/api/

Next, you need to find or create your list of categories for classifying the subreddits. This might include topics, themes, or niches. For example:

Technology
Travel
Fitness
Cooking
Gaming
Music
Art
Politics
Fashion
News

Once you have your data and categories, you can use generative AI to automatically classify your Reddit subreddits. This will help you to better understand your audience and tailor your content strategy to their interests.

Conclusion

Classifying Reddit community channels using generative AI can provide valuable insights into your target audience and help you to tailor your content strategy to their interests. By using the Reddit API and predefined categories, you can automate the process of identifying the topic or theme of each subreddit, saving time and improving the accuracy of your analysis. Try it out and see how it can benefit your marketing strategy!

Using AirOps to perform Keyword Identification

With AirOps, you can easily extract relevant keywords and phrases from your text-based data using the Keyword Identifier data app. Here's how:

Select "Keyword Identifier" from the Data Apps page. The input required for Keyword Identifier is the "text_field" which is the input text data.
Decide where you want the analysis to be performed and stored. The Keyword Identifier data app can be easily used in the AirOps Data App page and via API, but in this example, the analysis will be performed in Snowflake through an external function called AIROPS_KEYWORD_IDENTIFIER.

Here is an example SQL query:
```
SELECT
AIROPS_KEYWORD_IDENTIFIER(text_field) as result
FROM
your_table
```
Execute the keyword extraction analysis by running the SQL query. The output will contain an array of keywords and phrases extracted from the input text data.

Example Input:

"Hello, I am having trouble with my account. I cannot seem to log in and I have tried resetting my password multiple times."

Example Output:
```
"keywords": ["trouble", "account", "log in", "resetting", "password", "multiple times"],"summary": "A customer is having trouble logging into their account and has tried resetting their password multiple times."
```

Using AirOps to perform Sentiment Analysis

With AirOps, you can easily perform sentiment analysis on any text data such as reviews, support tickets, or sales calls using Sentiment Analyzer. Here’s how:

Select "Sentiment Analyzer" from the Data Apps page. The only input for Sentiment Analyzer is some text to analyze.
Decide where you want the analysis to be performed and stored. The Sentiment Analyzer data app can be easily used in the AirOps Data App page and via API, but in this example, the analysis will be performed in Snowflake through an external function called AIROPS_SENTIMENT_ANALYZER.

Here is an example SQL query:
```
SELECT
AIROPS_SENTIMENT_ANALYZER(text_field) as result
FROM
your_table
```
Execute the sentiment analysis by running the SQL query. The output will contain a sentiment score and sentiment summary, as well as a list of positive and negative keywords extracted from the input text data.
Input:
"I'm sorry to say that I had a terrible experience with your product. The customer service was unresponsive and the product didn't work as advertised."
Output:
```
"positive_keywords": [],"negative_keywords": ["terrible experience", "customer service", "unresponsive", "product", "didn't work", "advertised"],"score": -0.8,"sentiment": "Very Negative"
```

Using AirOps to perform Text Classification

With AirOps, you can easily perform classification using generative AI. Here’s how:

Select "Text Classifier'' from the Data Apps page. Below are the possible inputs for Text Classifier.text_field: The input text data.categories (optional): Categories can be specified as a comma-separated list. Leave empty for automatic determination.multi_category: Set to “true” if the text can belong to multiple categories, or “false” if it can only belong to one category.
Decide where you want the analysis to be performed and stored. The Text Classifier data app can be easily used in the AirOps Data App page and via API, but in this example, the analysis will be performed in Snowflake through an external function called AIROPS_CLASSIFIER.

Here is an example SQL query:
```
SELECT
AIROPS_CLASSIFIER(text_field, categories, multi_category) as result
FROM
your_table
```
Execute the classification analysis by running the SQL query. The output will contain a list of keywords extracted from the input text data that are relevant to the identified categories and a list of categories that the input text data belongs to based on the provided categories or automatic determination.

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