Instagram Data Challenge Submission

#1

Hello! For the Instagram Data Challenge, I used Kirsten Alana’s Instagram data to draw insights for my submission. I used data both counting from when Kirsten first started her instagram in 2010 to 2019.

I imported all the tables into Tableau and then when necessary used a join. I will show you exactly how I came up with my visualization since I didn’t use SQL.

  1. I imported the kirstenalanainstagram_instagram_media table into Tableau

I plotted the sum of all the likes count of all Kirsten’s posts on the Y axis and the hour of the created time on the X basis.

I plotted the sum of all the comments count of all Kirsten’s posts vs the hour of the created time.

Based on these two graphs it looks like the best engagement time is the afternoon around 2pm.

  1. Using Tableau, I did an inner join of Kirstenalanainstagram_instagram_media and kirstenalainainstgram_instagram_media_tags where id = Instagram media id

I plotted the sum of the average of the likes count of all Kirsten’s posts on the X axis and the hashtag on the Y axis and sorted from highest average to lowest.

I plotted the sum of the average number of comments of all Kirsten’s posts of all time on the X axis and the hashtag on the Y axis and sorted from highest average to lowest.

It looks like on average that #centralparkviews gets the highest average number of likes and #Parisgiveaway gets the highest average number of comments.

These findings made me interested in knowing the location of Kirsten’s posts. If #centralparkviews got the highest average number of likes, it make me guess that a good number of her photos must have been taken in New York.

  1. Using the Tableau, I did an inner join of Kirstenalanainstagram_instagram_media and kirstenalainainstgram_instagram_media_location where id = Instagram media id

The name of the location is on the Y axis and the number of posts containing that location is on the X axis.

Looking at the results, the top 2 locations are based in New York!

  1. I wanted to see who is the most engaging user to comment on Kirsten’s photos.

Using Tableau, I imported kirstenalanainstagram_instagram_comments

The name of the user with the most comments is on the Y axis and the number of comments from that user from of all time from the picture at that location is on the X axis.

I broke this down further by year

The count of the comments is on the Y axis and the number of comments from that user broken down by year X axis.

Other than Kirsten, the top 3 users who comment the most are Dante.vincent, leslie8989 and intuitiveartist and the engagement is highest around 2015-2017

This was a fun exploration of data. Thank you Panoply!

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