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DAT 375 Module 3-1 Assignment

This analysis uses quantitative methods to evaluate scraped data, identifying message and reshare averages per user and peak messaging times. Insights will guide improvements to our social media app's user interface.

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    Module 3-1: Choosing The Right Scripts Robert Wood Southern New Hampshire University 07/18/2024

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    M o d u l e 3-1: Choosing The Right Scripts After reviewing the problem for this analysis, the most appropriate data analysis technique to use in order to help with this problem would be a quantitative analysis. The purpose of the analysis that we are going to run is that we have been asked by our supervisor to use the provided scraped data set to find the average number of messages by a single username, the average number of reshares by a single username and finally the time frame that has the highest number of original messages. The data that we collect from this analysis will help our company to better understand how the competition has created the user interface for messaging on their social media applications to improve upon and build upon that for our own social media application. A quantitative approach to this problem is the most logical fit since we are looking for numerical data from the present and are not looking to make future predictions at this time. The scripts that are necessary and that were used to find the average number of messages by a single username and the average number of reshanes by a single username were pretty similar with only some slight changes in what was being pulled from the data and from where it was being pulled from. Meaning that the script essentially pul ed the same thing but from different columns/categories (messages and reshares). After running the script for the average number of messages by a single username using the following script we get the output that the average number of messages by a single username is roughly 945 messages. SELECT AVG(count) FROM ( SELECT username,count( - ) as count FROM assignment3_l.rwDod_table GROUP BY username ORDER BY count DESC

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