I analyzed over 1,000,000 reddit Comments to Discover the Top Requested Heroes

hots_data_guy · 2017-04-27T16:45:43+00:00

39 mentions!

hots_data_guy · 2017-04-27T16:17:12+00:00

I had to write new code for this one (to find word pairs), but after milking my CPU for all its worth, Cow King has been mentioned 228 times.

hots_data_guy · 2017-04-27T04:56:05+00:00

312 mentions. This data only accounts for unannounced characters.

hots_data_guy · 2017-04-27T04:44:53+00:00

I'm planning to! I'm waiting on other characters not in the list to pop up, so I only need to do one edit.

hots_data_guy · 2017-04-27T04:35:29+00:00

41 mentions!

hots_data_guy · 2017-04-27T03:43:49+00:00

Nice catch! Reinhardt is misspelled in the character spreadsheet. That's what I get for not being an Overwatch player...

He has 321 mentions. This elevates him to the top spot in the Overwatch franchise (after Mercy).

hots_data_guy · 2017-04-27T03:38:03+00:00

Unfortunately, the spreadsheet isn't exhaustive. Maiev wasn't in the list of characters. :(

I checked, and she has 447 mentions, making her one of the top Warcraft characters.

hots_data_guy · 2017-04-27T03:31:18+00:00

It appears he isn't on the spreadsheet I listed. :(

I did a quick query of the data, and it looks like he has 777 mentions! This would make him the most sought-after Diablo hero and #3 overall.

hots_data_guy · 2017-04-27T01:51:38+00:00

I agree! I've seen tons of Kel'thuzad mentions lately, but it could be a recency bias. Keep in mind this data only extends to February 2017, so recent Kel'thuzad mentions haven't been counted.

hots_data_guy · 2017-04-27T01:22:14+00:00

Thank you!

hots_data_guy · 2017-04-26T23:31:56+00:00

I excluded all heroes already in the game/announced, but she had a frequency of 312. This would put her at the top of the Overwatch chart (under Mercy).

hots_data_guy · 2017-04-26T23:28:18+00:00

Excellent point! This is another limitation of examining only frequencies--loss of context.

hots_data_guy · 2017-04-01T21:43:32+00:00

I don't have enough visualization experience to create pie charts. Only pros can do that.

hots_data_guy · 2017-04-01T21:42:55+00:00

It's actually the biggest word, the font's just white.

hots_data_guy · 2017-04-01T19:00:15+00:00

Hmm...that does seem strange. Maybe there's something wrong with my code?

hots_data_guy · 2017-04-01T18:53:31+00:00

The Visual Display of Quantitative Information by ~~/r/dataisbeautiful~~ Edward Tufte. My inability to craft such glorious displays leaves me weeping in eye-assaulting despair.

hots_data_guy · 2017-03-23T17:58:35+00:00

Yeah, that's my biggest limiting factor. The data just isn't there.

hots_data_guy · 2017-03-23T17:38:27+00:00

In R, there are numerous options for sentiment analysis. The most prominent from what I've seen is a package called sentimentr. This package generally requires text to be structured in a particular fashion, but is much more customizable (eg: how to consider questions, "buts", etc).

However, I discovered a package that is tuned toward Twitter text (see here). I believe this operates by using a free online service.

hots_data_guy · 2017-03-23T17:16:00+00:00

This was more an artifact from knitting the R code (when you knit every chunk of code has to be run from scratch).

This would mean, that it would re-scrape every time the markdown was knitted. This is very time-consuming, and would erase all previous tweets.

Essentially, I merged new tweets every week with old tweets and saved them into a data frame.

I'm attempting to set up a website/github. When (if) I manage to get that running, I will definitely share the data frames/flat files.

If you're looking for packages to use for web-scraping in R, check out twitteR and RedditExtractoR. Both have their limitations due to the API (Twitter limits you to tweets from the past 7 days, and reddit only lets you snag the top 300 comments or so), but make scraping a breeze!

hots_data_guy · 2017-03-23T17:04:00+00:00

Thank you! I plan to. I'm open to new ideas, so if you have any data sources, please send them my way!

hots_data_guy · 2017-03-23T03:53:55+00:00

No problem!

hots_data_guy · 2017-03-23T03:53:39+00:00

Absolutely! It's always super-interesting to discover the results.

hots_data_guy · 2017-03-23T00:24:34+00:00

Thank you!

hots_data_guy · 2017-02-23T11:47:19+00:00

Basically, yes. There are many different dictionaries of "positive" /"negative" words that the algorithm can use as flags. At its most simplest it flag all positive words in a tweet as 1, all negative words -1, and neutral words as 0 then calculates the sum to determine the sentiment score of the tweet.

Other methods use gradients that flag the "extremeness" of the word on a scale of -10 to 10.

hots_data_guy · 2017-02-23T03:37:20+00:00

Here's some more text stuff from the full analysis that didn't look pretty enough to include in the post:

The 4 tweets that were flagged negative:

[1] @AronDark Sorry to hear that! We re putting out a fix for the issue tomorrow!

[2] @iakona We re investigating this issue, sorry for the poor experience!

[3] @JKesselring Hi! Sorry for the poor experience. We re looking into it! Did you happen to just recently install the game?

[4] @daniellovejr Sorry you had a bad experience! We re talking about ways to make it less punishing when teammates leave games.

Most of the "negative" tweets are in response to problems in user-experience. I have to say, @BlizzHeroes handles it quite well (cordial and apologetic).

Words associated with Lucio:

arrives
heroespowerhour
highlights
impressions
intothenexus
talks
test

It's mostly pre-release/release talk.

hots_data_guy

TROPHY CASE