#StackBounty: #python #r #data-mining #sequential-pattern-mining Which one to choose to identify patterns of user activity: Sequence an…

Bounty: 50

I have the following user activity data that where for each user the activity type they were engaged are recorded along with the phase:

User |  Phase |  ActivityType  |  Date
321     1        A                12/20/2020 15:00
321     1        B                12/20/2020 16:00
321     2        A                12/21/2020 12:00
321     1        C                12/21/2020 13:00
321     3        B                12/22/2020 11:00
322     1        A                12/20/2020 15:00
322     1        A                12/20/2020 16:00
322     2        B                12/21/2020 12:00
322     1        C                12/21/2020 13:00
322     3        D                12/22/2020 11:00

For each user, I also have the satisfaction score about the application.

User | Satisfaction
321    90
321    60

What I want to see is if there are any emerging groups of users with a certain pattern of activities. Then, I want to compare the satisfaction scores across these groups to check if the specific pattern of activities yield higher satisfaction or not.

To perform this analysis, I identified two approaches: process mining (with PM4PY, python library), and sequence analysis (with TraMineR, an R library).

However I am not sure which one would fit better to my needs. I am a total beginner in both areas. Any insights to help me make a good decision here?


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