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OpenSentiment - Interactive Visualization, Now for Any iOS App
Hi all,
I decided to take a couple days and look more deeply at the feedback so far for Fiddlewax by building a visualization. In the process, I realized it could work with any social (free text) dataset, so it seemed logical to make it open source so others can play with it, too.
It's called OpenSentiment and includes a combination of text analysis algorithms (determining the "sentiment" of reviews) and interactive visualization (click on words and phrases to see the context of how they appear in the data).
You can load the example Fiddlewax review data and play around with it here:
http://akumpf.github.io/OpenSentiment/#./example_csv_data/fiddlewax_app_reviews.csv
OpenSentiment is released as open source on GitHub if you want to hack around with it for your own projects and datasets. View the source and read more here:
Edit: Now you can look at reviews for any iOS app using its APP_ID. More info on the GitHub page.
https://github.com/akumpf/OpenSentiment
Cheers,
Adam
Comments
This is... interesting. So you manually entered review data into a database for it?
Yeah, I was just curious to explore the data in different ways. It's not really intended to scale to huge datasets or be a drop-in replacement for other app review tools that poll for review data on a daily basis.
That said, if you have review data in a standard format, it should be a pretty simple transformation to put it into a 1-response-per-row CSV file.
Anyone know of a public API for downloading all reviews for an app? I'd be curious to automate a process that could create the appropriate CSV file for OpenSentiment
Ok, now you can use OpenSentiment for any iOS app
To load from a specialized JSON source, use a comma separated list in the hash. For iOS, most but not all ratings seem to appear. Loading reviews for specific iOS apps is simple -- just use the hash #ios,APP_ID_1,APP_ID_2,...
Replace APP_ID in the url with the ID(s) of the apps reviews you want to check out.
For example, here's OpenSentiment with Fiddlewax Blue, Fiddlewax Yellow, and Fiddlewax Pro all shown together.
http://akumpf.github.io/OpenSentiment/#ios,814998374,866070342,905878913
Happy analyzing!
@adsmkumpf in quickly looking at your analysis of the Fiddlewax apps, it seems to me the next step would be to do this for a large number of apps and see what terms are common to all apps, those specific to music apps, etc. . . so you can then refine the analysis by filtering out commonalities and spotting trends. Developers could then have even more insight into what's significant in their apps for the people who use them. It'd also be very useful to link review data to sales so that you can see what proportion of people who purchase an app respond and spot any trends related to perhaps niche apps versus apps with a broader appeal in terms of the feedback you get from users. It'd be a very powerful way to then quantify how app reviews effect sales of emerging apps so that developers can then identify factors that lead to successful apps versus apps that tank.
Don't know how I missed this. This is nice work Adam!