How People On Reddit Talk About Epilepsy

As a technologist, I’m fascinated about how people use social media. It’s such a vast space but people find places where they can make connections around any number of topics. Social media has fostered revolutions, saved lives, but also taken them. It enables freedom of expression but also allows an unprecedented level of hatred. Like a hammer, social media is a tool, and it’s up to humanity to use it to build or to destroy.

I read an article that described a language analysis done on comments from Reddit. Reddit is a community website that aggregates content. It also allows members to share, rate, and discuss the content. I thought it would be interesting to see how people on Reddit talked about epilepsy.

Why does it matter?

If you’re reading this post, you may have been lead to it by Twitter, Facebook, or Medium. Maybe you subscribed to the blog. In any case, you are using technology and the Internet to consume information. And there is a lot of information out there…some good, some bad, some supportive, some not. These types of analyses aren’t perfect, but they can provide some interesting insights.

I’m old enough to be able to navigate these platforms and decide what to take and what to leave. While my son is not of Internet age yet, he will be soon. And he’ll be more likely to look to social media for support. The more I know about the different systems, the abler I’ll be to guide him as he explores them.

More generally, though, these types of analyses can be helpful to see what aspects of epilepsy people are talking about. Or, not talking enough about.

What data did I look at?

For this project, I grabbed comments from March 2017 that contained the word “epilepsy“. That gave me 3,046 comments out of about 79 million (0.0038%). Literally, a drop in the bucket, but enough for a simple analysis.

Number of comments by day in March 2017

Here is how the epilepsy-related comments were distributed throughout March.

epilepsy reddit nlp google sentiment

The big spike on March 22 was partly due to a question in AskReddit. AskReddit is where posters ask and answer “questions that elicit thought-provoking discussions”. The spike was the result of responses to the question “What are you sick and tired of having to explain to people?.” I can imagine people living with epilepsy having an opinion on that question.

Which subreddits are the most active?

Next, I wanted to break down the comments by the group they were posted in. On Reddit, the groups are called “subreddits”. Those discussions helped the AskReddit subreddit lead the comment count for epilepsy-related posts. The subreddit dedicated to discussions about epilepsy came in second.

epilepsy reddit nlp google sentiment

What adjectives do people use when they talk about epilepsy?

Besides looking at simple numbers, I wanted to analyze the comments themselves. I ran them through Google’s Natural Language (NLP) API to see what I could learn. NLP takes a sample of text and breaks it down into parts of speech and sentiment.

First, I looked at the parts of speech. Here are the top adjectives most used in conjunction with the word “epilepsy.”

epilepsy reddit nlp google sentiment

What is the sentiment of the comments about epilepsy?

Next, I wanted to add the sentiment piece. The NLP looked at each comment and to try to infer if it represented a positive or negative sentiment. “I won’t let epilepsy get me down” is an example of a positive sentiment. “I have epilepsy and am depressed” expresses a negative sentiment. I wondered if the adjectives used changed depending on the sentiment of the comment, and they did.

For comments characterized as positive, words like “good”, “great”, and “best” were included.

epilepsy reddit nlp google sentiment

For negative comments, “bad”, different”, and “severe” made the list.

epilepsy reddit nlp google sentiment

I also wanted to look at the sentiment across the different groups. The chart below shows the average sentiment of the epilepsy-related comments by subreddit.

epilepsy reddit nlp google sentiment

Again, a positive score reflects an overall positive sentiment of the comments. Interestingly, the big negative score on the chart is for the subreddit “KotakuInAction.” The group relates to the “GamerGate” controversy and other gaming and Internet issues. The thread that contained the epilepsy comments related to the Eichenwald case. That was where a journalist with epilepsy was sent a seizure-inducing twitter message.

What else do people talk about when they talk about epilepsy?

Finally, Google’s algorithm also provides other topics (entities) that are discussed in text. Here are the most common entities mentioned in conjunction with epilepsy on Reddit.

epilepsy reddit nlp google sentiment

Let’s look at January through March…

Since the data was available, I ran a few of the reports for the first three months of 2017, as well, to see if anything changed.

First, here are the number of comments for January through March.

I also wanted to see how different the entities report was over the three months. There was a lot of overlap from the March chart, showing that conversations about those entities are likely normal.

Finally, I also looked at the occurrences of specific references to a handful of positive and negative terms that often come up when speaking about epilepsy.

Looking at the two charts, clearly, references to medication, side effects, and depression were often discussed in the comments on Reddit.

What’s next?

This project was a first look at using natural language processing techniques to analyze social media posts about epilepsy. There are a number of applications for such technology, and it will be interesting to explore more sites and using different algorithms and techniques. If you have any thoughts or suggestions on other ways to look at the data, please leave a comment below.

If you’re interested in doing your own analysis, you can find the source code and other information on my GitHub page. A shout-out to Sara Robinson for her article, which was a guide and huge inspiration.

The Lonely Record – A Story Of Data In Epilepsy Diagnosis

Somewhere in a cluster of servers in windowless rooms spread around the world, there is a Great Machine. On that machine, there lives a database. In that database, there is a table, and in that table, there is a record about my son. The 1s and 0s in that record contain an anonymous listing of a six-year-old boy. Those bits and bytes also contain data of expressed genes captured during an exome sequencing.

In the same database, there are records of thousands of other children that have had their exome sequenced, too. Each individual record has at least one common attribute with all the other records…the child that the record represents has epilepsy.

The goal of the exome sequencing is to identify one of the known genetic variations that is known to cause seizures. If that happens, patients can benefit from those that came before. A potential treatment plan identified by other patients with the same genetic condition might provide a more targeted approach for the newly matched patient. It might also offer some insight in to prognosis. For better or worse, it may at least give some answers.

For the new records that are placed in to the database that are not matched to a known genetic cause, they sit unattached and alone. These records lack causation and, in their unjoined state, they also lack correlation. There are no patients that came before, no best practices or lessons learned. There is no prognosis. There are no answers.

My son’s record is that way. It rests alone in a database, somewhere in the world, on a cold, metal server in a windowless room, waiting to be called. Waiting to be joined with another record. Waiting for correlation. Because with correlation, there can be association. With association, there can be coordination. With coordination, there can be answers.

Every six months, the Great Machine tries to use new discoveries, new cases, to find patterns that were previously unseen or unknowable. It calls out to each record, looking to find those that it may bestow the gift of correlation. For most, there is no correlation, no gift, and they return to their lonely state until they are once again called upon.

Maybe someday, my son’s record will find a partner. A commonality between another record in a database. A non-uniqueness in the universe. In all likelihood, the result of a match will not produce a cause for the seizures. It may, however, start to provide correlation between cases that can be studied further.

To a lonely record, it’s at least something.


Exaptation And Innovation In Epilepsy

This post is part of the Epilepsy Blog Relay™, which will run from March 1 through March 31. Follow along and add comments to posts that inspire you!

In evolution, the term exaptation refers to a trait that has evolved for one purpose but is subsequently used to serve another. The classic example is feathers, which evolved in birds as a way to regulate body temperature but were later adapted for flight.

The same process is happening in technology, including technology related to seizures and epilepsy. Already this week, other bloggers writing about technology and innovation in epilepsy have described exapting technology developed for one purpose for the treatment of epilepsy. Whether it is how Whitney Petit described how she uses her fitness wearable to control her nocturnal seizures or how a sensor to measure the “fight or flight” response became part of the Empatica device indented to detect seizures, advances in general areas of technology are also spurring progress in the managing and controlling of seizures.

I think a lot about technology. My day job is to identify trends in technology and peer into the future to try to predict where things will be in five years, ten years, or even further in to the future. I also think a lot about epilepsy. My six-year-old son has refractory epilepsy, which means it’s not controlled with medicine. Being a technologist and an engineer, my natural inclination is to turn to technology to help my son, even if it is not currently able to offer any answers.

There is one trend that I have been focused on most recently, and that is the development, availability, and shrinking size and cost of sensors. For example, companies are putting gyroscopes that measure angles and tilt and accelerometers that measure acceleration in wearable devices simply because they can, because the sensors are so small and so inexpensive. There are already components smaller than a watch battery that can detect movement and relay information to another device. Smart textiles provide digital fabric that will allow sensors to be stitched seamlessly in to clothing.

When I look in to the future, I see the ubiquitous nature of sensors in everything from watches and rings to shirts and shoes as manufacturers attempt to measure, collect, and report on our every step, breath, and literal heartbeat. I also see unlimited potential to repurpose these objects in ways that will make my son’s life better by helping him manage his epilepsy. The ultimate goal is to remove the friction imposed by requiring a specific device to be worn for the detection of seizures and to, instead, put that capability everywhere.

There are challenges with making this happen. Manufacturers must open their platforms and allow communities to leverage the data or sometimes reprogram devices for new tasks, such as detecting seizures. Testing for medical devices is rigorous, necessary, and expensive. But, in many ways, the ground work will be done. The sensors and devices necessary to do the work will be out there already, and we will just need to find creative ways to take advantage of them.

And that is where you come in. Even if you are not a technologist or an engineer, you are reading this post, most likely, because you or someone you know has epilepsy. In order to make the future happen, it will be up to people like you to create it. The next time you pick up a new gadget, ask yourself how it can be repurposed to solve a different problem. Instead of detecting how many steps you are taking, observe the physical characteristics of your child’s seizures and ask yourself how the accelerometer in that device might be able to detect a myoclonic seizure or a fall. The next time you read about how a new athletic top can measure the performance of an athlete, think about how those same measurements might be able to detect the increased heart rate or breathing rate that happens during a seizure.

I think a lot about technology, and I want you to think a lot about technology, too. Because there is no one better equipped to find creative uses for this new technology in the treatment of epilepsy than those of you that are living it every day.

NEXT UP: Be sure to check out Jade Dolby – The Art of Living with Epilepsy for more on Epilepsy Awareness.