What to say about Reddit. On the one hand, it represents how online communities can bring people together from different walks of life, with diverse experiences, from all over the world to one place where they can visit their favorite subreddits based on their interests like /r/Google, /r/Gaming, /r/Sports and on and on. Or it can be a place to discuss and learn new things like /r/todayilearned or /r/askreddit. A few of the more niche subreddits I myself follow include /r/amoledwallpapers, /r/prequelmemes (Hello there!), and /r/movies. On the other hand, Reddit often gets a bad reputation when it comes to its online users (redditors) who can often be characterized as a hivemind collective. Downvotes are supposed to be used as a signal that a comment is not constructively contributing to a discussion but are more often used as an “I don’t like / agree with this comment” button. Redditors can be painted as a negative bunch who only complain and rip apart people, companies, or products who have wronged them or are generally bad.
I decided to take a deeper look into how Redditors offer suggestions to one of the biggest and most famous companies on Earth: Google. I’ve also noticed through my time online, that people interested in tech are also notoriously critical of companies and products (like on YouTube) so this analysis may yield some not-so-nice things of what people have to say and how they feel about Google. I am a Google fan, admittedly, and am in love with their Pixel line of phones but Google has had a fair bit of controversy on both the hardware and software side. We’ll try to see if Redditors have some solid business advice for Google or if they live up to their stereotype.
Getting the Data
First, with some help from this article here: http://www.storybench.org/how-to-scrape-reddit-with-python/ we can set up our coding environment. The guide is very straightforward and I just had to tinker with some parts of the code to specify what subreddit I wanted
import praw import pandas as pd import datetimeas dt reddit = praw.Reddit(client_id='privatestring', \ client_secret='privatestring2.0', \ user_agent='googleshould', \ username='dontsharethis', \ password='dontsharethis2.-') subreddit = reddit.subreddit('Google') top_subreddit = subreddit.search('Google should', limit=500) topics_dict = { 'title':[], \ 'score':[], \ 'id':[], 'url':[], \ 'comms_num':[], \ 'created': [], \ 'body': []} for submission in top_subreddit: topics_dict["title"].append(submission.title) topics_dict["score"].append(submission.score) topics_dict["id"].append(submission.id) topics_dict["url"].append(submission.url) topics_dict["comms_num"].append(submission.num_comments) topics_dict["created"].append(submission.created) topics_dict["body"].append(submission.selftext) topics_data = pd.DataFrame(topics_dict)
If you look at the guide you can see where I changed things like my client ID, client secret, and username/password for obvious reasons. I specified I wanted to get hits from /r/Google that contain the phrase “Google should” which should capture most criticisms, suggestions, and comments on Google products. I admit this isn’t an exact science but it’s just to get a feel of the sentiment out there. I also could have used an R-based sentiment analysis but I’ll have to learn how to do that some other time.
My code spit out a table which I formatted into the table below:
After doing this process 2 more times for the /r/Android, /r/GooglePixel subreddits (I know there are other Google-related subreddits out there but these are the largest ones) I compiled my data into a csv and was ready to hand code the sentiment and general topic (hardware, software, business, misc.) of each post. This took an hour or two but now my data is ready to be used!
Let’s see the initial statistics!
First though, what does positive or negative mean? And what are the topics that I grouped things into?
Sentiments and Topics
Positive: Generally praising products and offering constructive feedback and suggestions
Negative: Generally disliking products and contain rants, angry messages, or venting of frustration
Business: Related to Google’s business decisions on privacy, policy, strategy, and/or marketing
Software: Related to Google’s software for Android, Assistant, Maps, Etc.
Hardware: Related to Google’s hardware like Pixels and Google Homes
Misc: Sometimes jokes, sometimes funny suggestions (not serious)
Positive vs. Negative Posts
Comments by Topic
googlecoded.groups(['Topic, 'Sentiment'])
Positive vs. Negative Posts by Topic
googlecoded.where(5, 'Negative').group('Topic') googlecoded.where(5, 'Positive').group('Topic')
Posts on software are also overwhelmingly the majority. This can be easily explained: Google was/is a predominantly software focused company. Google did not focus on hardware until the release of the Pixel phones or Google Home devices which were released in 2016.
Hardware Suggestion Posts Over Time
A sharp increase from 2015 with no hardware posts to 2016 with 9 when the first Google flagship phone and Assistant-based hardware were released. Then, another sharp increase in 2017 when the Pixel 2 and Google Home Mini were released. The Pixel 2 XL was arguably the most controversial phone of 2017 due to its “blue-shift” screen flaw from LG’s OLED smartphone screens. With big tech reviewers like The Verge (they pulled their score after users reported the blue-shift issue) and MKBHD (he said it wasn’t a huge issue) being divided on the issue, Pixel 2 XL users were just as polarized. Many users on /r/GooglePixel were up in arms and multiple posts described how they were on their 4th or 5th Pixel 2 XL. Definitely not the best year for Google, but it was a solid upgrade from the Pixel 1 and the Pixel 2 (regular) had no screen issues. The Pixel 3 was leaked to the moon and back so that may be why there were fewer posts on hardware suggestions in 2018 because the rug was pulled from under Google.
Positive vs. Negative by Year
googlecoded.where(5, 'Negative').group('timestamp').plot('timestamp') googlecoded.where(5, 'Positive').group('timestamp').plot('timestamp')
Looking back at the overall yearly data, it looks like there’s some interesting trends happening and one in particular that I did not expect. We can also ignore the large drop from 2018 to 2019 as the year just started. It seems that when it comes to suggestions, Redditors are overwhelmingly positive, in general. A few underlying factors may be biasing the data towards trending positive:
1. Those subscribed to these subreddits may be fans/supporters of Google products and services so they will voice their opinions positively.
2. Having a complaining or whining tone while writing a post may net the OP more negative downvotes since they present their opinions in a polarizing manner rather than asking for a discussion of views.
3. Google has yet to suffer a scandal on the scale of Facebook’s data and privacy leaks (which is continually revealing new facts and staying in news headlines).
It may be that the OPs understand that if they want their suggestions to be taken seriously on the off-chance that a Googler is perusing the forums (I would wager that most Googlers use/read Reddit), a positive tone will go much farther than a negative one.
The growth rate of negative posts year over year may be a point of concern for Google. Since 2013, there was some growth in negativity but from 2016 onwards, the growth rate of negativity skyrockets. Positive posts have also climbed but seem to have plateaued from 2016. In absolute terms, positive still far outweighs negative, but relatively, negative posts are growing quickly which may have been brought on by Google’s entrance into the hardware space and the release of their Pixel line. The 2nd and 3rd iterations of their device were not received as well as many expected.
Now let’s see which positive and negative posts were the most upvoted. We won’t be able to see the most downvoted because Reddit doesn’t share that with the API, anymore (allegedly). So 0 point posts could be -1000 or simply 0 but we can’t tell.
#show the most upvoted posts (pos and neg) googlecoded.sort('score', descending = True) mostp = googlecoded.sort('score', descending = True).where(5, 'Positive').take(0) mostn = googlecoded.sort('score', descending = True).where(5, 'Negative').take(0)
The most upvoted positive post is: “10 Reasons why Google Should buy Radioshack, ‘Google could Immediately Have a Bigger Retail Presence Than Apple with 5,000 US Stores, a Rejuvenated Workforce, and a Lucrative Business Model Selling Carrier Android Devices and Accessories’” from 2015 at 10,594 upvotes.
But I don’t think we should judge everything based off just the top post, others may be close to them in score. The next four scores are 10,367 (Google Play Store), 5,598 (Google Play Store), 4,845 (Assistant/Google Now), and 3,884 (Google Maps) upvotes. Now the picture is a bit clearer, four software and one business recommendation.
The most upvoted negative post is: “Just as Samsung got a ton of flak for restricting the extra button on the S8 to Bixby, Google should get flak for restricting the squeeze functionality in the Pixel 2 to Google Assistant” from 2017 at 4853 upvotes.
If we look at the next top four negative posts we get, 4,445 (Google Play Store), 4,432 (Google Play Store), 4,208 (Google Play Store), 2,506 (Google Pixel). Also four software and one hardware recommendation.
With this in mind, let’s also take a look at the average upvotes for each category which we can further break down by year.
Average Upvotes per Topic
Averages here bring things into better perspective but remember that there are a good deal of 0 upvote posts where we can’t quantify their true scores. Ignore the misc. category as there’s only a handful of posts. Looks like Reddit doesn’t think Google’s Hardware division isn’t doing so hot.
If we break it down by year, we can see which sentiments were more prevalent during a given year. Below is the code used to organize the data into positive/negative averages, and the percentage of positive/negative upvotes every year.
#positive averages most_popularp = googlecoded.select(1, 4, 5, 6).group([ 'timestamp', 'Topic', 'Sentiment'], sum).where( 'Sentiment', 'Positive').sort( 'score sum', descending = True ) most_popularp.drop('Topic').group(['timestamp', 'Sentiment'], np.average).show() #negative averages most_popularn = googlecoded.select(1, 4, 5, 6).group([ 'timestamp', 'Topic', 'Sentiment'], sum).where( 'Sentiment', 'Negative').sort( 'score sum', descending = True ) most_popularn.drop('Topic').group(['timestamp', 'Sentiment'], np.average)
year_score = googlecoded.pivot('Sentiment', 'timestamp', 'score', sum) Total = year_score.drop(0).apply(sum) year_total = year_score.with_column('Total', Total) def percent(x): return np.round (x / Total * 100, 2) year_percent.drop(1, 2).with_columns( '+ %', percent(year_total.column(2)), '- %', percent(year_total.column(1)). show()
Average upvotes by Sentiment
Percent of Upvotes by Sentiment
Another interesting trend of rising negativity. It’s more visible after we weighted the Sentiment category by the averages of each year and laid it next to the percent of upvotes per year. This confirms that there is a rising sense of negativity in the past few years and that 2019 is not off to a good start. We can see here again that 2017 was a particularly rough year for Google, most likely because of the Pixel 2 XL issues and it marked the beginning of the negative trend we’re seeing. Google has recently branched out into different industries like hardware and AI but it needs to ensure that a good user experience and customer satisfaction for each of their new products. Google can’t afford to stretch itself thin when aggressively pushing its new products. Google needs to calculate the risk of pushing a fragmented strategy, having poor support, or releasing a poor product. These would all be a major blow to Google’s good progress in the past few years. From just a search engine and advertising company, Google is now in millions of homes and people’s pockets just in the past couple of years. Now, it needs to cement its firm foothold in the market and look to expand.
Recommendations
Judging by this data, there’s a few areas where Google can improve and it should be concerned with recent growing negativity. The growth rate of positive feedback compared to negative feedback in the past 3 or so years has been much lower so it is signalling a sea-change in public opinion, but if Google addresses some of the bigger issues it may be able to keep the negativity at bay.
Overhaul of the Google Play Store and stricter regulation for how developers advertise with and interact with customers. Out of the top 5 posts in both negative and positive categories most focused on the Google Play Store. Now, these complaints are not directed at Google itself, but users are asking for better policies and guidelines on how people on both the buying and selling side of apps interact. A verified or trusted creator program would be helpful for people looking to buy apps where creators with over 10,000 or so downloads and good ratings could get a seal of approval from Google. Or Google could increase moderation of the Play Store for developers that constantly put out subpar or ad-laden apps.
There is clear demand for a greater on-the-ground presence by Google. There are occasional pop-up stores around the country, some in NYC and Chicago, but often times you cannot buy the products featured or they are managed by third-party sellers. Even Samsung has ramped up their physical store presence and if Google is looking to make a dent in the hardware space, they are going to need more than just digital marketing. Ads for the Pixel are also somewhat misleading where they say “available only on Verizon” but there are financing options (because Americans often lease their phones) on Google’s own carrier Google Fi and on their store website. A non-Verizon customer will rarely ever walk into a Verizon store to look at exclusive phones. Verizon commands an impressive 34.4% share of US mobile customers but Google is still missing out on 65.6%. A few dedicated hardware stores in major cities that stock Google products will bring in new customers who want to actually touch and feel Google products.
Fuller customization of software. Android is better than iOS at this but users are asking for more areas where they can take full advantage of the features offered. Users want remapping squeeze functionality, dark mode everywhere, and customizing colors of contacts just to name a few. Some of these suggestions should not be considered if they disrupt the flow, ease of use, and design language of Android and may overwhelm a user, but others should be more seriously considered as QoL (Quality of Life) changes.
The most recent change of rising negativity should definitely concern Google but 2019 is still young. Google’s recent roll-out of Duplex, upcoming Pixel 4, and new version of Android will be key in keeping positivity high. Google needs to focus on marketing and delivering solid products to curb rising negativity. Mediocre performance will not exasperate negativity but it will do nothing to mitigate it.