Building a Serverless Dashboard for Real-time Social Media Data Analysis

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In this video tutorial, you'll learn how to create a serverless dashboard to analyze and visualize social media data in real-time using AWS Lambda functions and MongoDB.

Create Lambda functions

1. Open AWS Console. Search and open AWS Lambda Service.

2. Create the first Lambda function

   1. Name: collect_tweets

   2. Runtime: python 3.9

   3. Leave everything else as default and create the function

3. Upload the collect_tweets.zip

4. In Configuration/General configuration:

   1. Memory: 500 MB

   2. Ephemeral storage: 1000 MB

   3. Timeout: 1 min

5. In Configuration/Environment variables, create the following variables and provide corresponding values:

   1. api_key

   2. api_secret

   3. access_token

   4. access_secret

   5. mongodb_connect

   6. database_name

   7. geocode

   8. q_parameter

6. In Test, create a new event to test the function.

7. If the test is successful, add a trigger:

   1. Source: EventBridge

   2. Create a new rule

   3. Name: every5min

   4. Schedule expression: rate(5 minutes)

8. Create the second Lambda function

   1. Name: sentiment_tweets

   2. Runtime: python 3.9

   3. Leave everything else as default and create the function

9. Upload the sentiment_tweets.zip

10. In Configuration/General configuration:

    1. Memory: 500 MB

    2. Ephemeral storage: 1000 MB

    3. Timeout: 1 min

11. In Configuration/Environment variables, create the following variables and provide corresponding values:

    1. mongodb_connect

    2. database_name

    3. lang

12. In Test, create a new event to test the function.

13. If the test is successful, add a trigger:

    1. Source: EventBridge

    2. Use existing rule: every5min

Create a MongoDB Dashboard

1. Log in to the MongoDB website and find the database that contains the collected tweets.

2. Open MongoDB Chart and add a dashboard. Use the final project database as the data resource. Create the following charts and add filters to all charts to show the data from the last 60 minutes.

   1. A number chart to show the total number of collected Tweets

   2. A line chart shows the number of tweets with different sentiments over time. Use the local time zone.

   3. A word cloud to show the top 50 popular hashtags

   4. A bar chart to show the top 10 active Twitter users

   5. A table to show the Twitter texts, number of favorites, positive scores, and negative scores.