Challenge #89: Analyzing Social Data

[Kenda]

Spoiler

I looked at which hashtag was used the most, which day had the most hashtags, and which person used the most hashtags.

[Simona]

I might have missed some cleansing with this, but I guess I will realise it better when I will plug the data into Tableau - most likely tomorrow :)

I think it is an interesting challenge as at least myself I did not deal often with social data and they indeed have a peculiar structure!

Below my solution, I think I got them ready to visualise and analyse :)

Spoiler

First observation, I wonder why I did not just use 1 input tool, I guess I was lazy ahah. :) I used regex for a couple of columns (hashtag and tweet) to remove some bad characters, removed null/ empty hashtags and also made sure to tag including the filename in each input so that I could know at the end where each row was coming from. I ended up grouping on some fields I think I will be interested to analyse. 

[JefBus]

Ok, this is my first submission for the Weekly Challenges,

I Guess mine is not as squeaky clean as most, I was doing  some generic calcs and ETL for conventional charting, and suddenly realized this might be a very interesting challenge to  try out Alteryx's network analysis tool, so from there, i got to this point :) ( the basic ETL are the orphaned flows on top) So started iterating  and testing little other blocks, and got kind of messy, just like a kid having funn with paint

The Idea: visualize who were the primary influencers,

The solution, once visualised, is not that super handy, as i run into trouble  graphing every tweet, so here i limited it to the first 1500 records, sorted chronologically. 

The last  pic is a Data-Dandelion of social importance :) 

[Chirag09goa]

This is my first ever post on this community and second challenge since signing up yesterday

[SeanAdams]

Welcome Chirag - first post of many I hope!

[LordNeilLord]

I kept it simple

Spoiler

[estherb47]

Playing catchup.....

I decided to focus my analysis on time and influencers. So, cleaned up the time and date fields to be actual time and date format, and then combined them into one field. 

Created a new field to determine who was being retweeted, and then counted the number of times each was retweeted (higher number = more of an influencer). 

Finally, parsed the unique tweets into rows based on hashtags for a hashtag analysis. Outputs all go into .tde format to be fed into a Tableau dashboard.

[estherb47]

Updated my workflow with a little fuzzy matching to normalize at least some of the hashtags

[LandonG]

Solution attached.

[PhilipMannering]

Solution attached.

Spoiler