Emerging Scholars Fellowship

Meet the Scholar

This post was written by Alex Budenz, one of our 2017 Emerging Scholars. Over the course of the next few months, Alex is working to quantify the stigma and social support surrounding bipolar disorder on the social media platform, Twitter. You can read more about her project here

Hi everyone! My name is Alex, and I’m a third year doctoral candidate in the Dornsife School of Public Health at Drexel University. My Emerging Scholars Fellowship research focuses on social media communication about mental health conditions (specifically bipolar disorder) and how stigma and social support are carried through social networks. As much as I love research, there are other things that I love and that shape my identity.


First, I have always been passionate about all things art-related. I have played music all of my life, have been a photographer for about 10 years, and am always trying different creative outlets, like painting and graphic design.

I am also a long distance runner and am fascinated by the ways in which running brings together the connection between the mind and the body, allowing us to reason our way in and out of physical pain and endurance. Lastly, one of the things that has always been a trademark of mine is drastic hair changes. I have had bright pink hair, Mohawks, super long, Wednesday Addams hair, and everything in between (though now that I’m teaching and stuff, I’ve had to tone it down just a bit!).


Right now, I’m in full-time research mode. I became interested in my research topic, because, not only is bipolar disorder a deeply personal topic, but because I also have a background in multimedia and have always taken on projects that explore the relationship between media, identities, and mental health. In addition, the idea of using emerging technologies and methods to build up evidence to enact change is something that keeps my energy up every day. I think that my project can make an impact, because mental health is often on the “fringe” of the public health field, is devalued, and is inextricably tied to wider social structures, and it’s time that people who can stand up and advocate for mental health stand up and advocate! Also, I’m lucky that A LOTTTT of people use social media, and so, this is a tool that is widely known, accessible, and ready for us to leverage for good.

My research has gotten mixed reception. In public health, things tend to be very intervention focused and very focused on tried-and-true methodologies that allow us to present to decision-makers and say, “hey! We did this and then this happened, and we can measure it!” However, because I am working with some unconventional methods (Twitter, Instagram), we haven’t exactly figured out the full extent to which these things can be leveraged and how we can use them to enact change. SO, I’ve gotten responses as varied as “wow! I would actually want to read about this, because it’s something I’m familiar with and know how to use!” to “I just don’t believe in this as a viable research method.” This mixed reception has sometimes caused me to doubt myself, because, I’m not going to lie, validation from others feels great. Self-doubt might actually be one of the major setbacks that I’ve faced in this process.

Another one, which I won’t call a “setback” as much as a “challenge that’s taking over my life” is teaching myself machine learning. Machine learning is basically teaching the computer to think the way that you have about a problem, so that you can get it to carry some of your workload, in terms of analyzing the content of things (in this case, Twitter posts). I have hundreds of thousands of tweets on these topics, and I can’t possibly analyze the content of each one! So, machine learning is extremely useful, but very hard to learn for someone with a media/arts/clinical background.

My most important finding (at this early stage) has been that it’s pretty difficult to put objective meaning to social media content. You start out with a bunch of categories to put these tweets in, and these usually come from past works. However, when you actually get into examining these tweets, you find that they can mean ten things at once, and it’s your job to do your best to make meaning, even if it means that you have to choose simpler ways to categorize them. That really sounds abstract, but if you’re interested in that process, go on Twitter, and look at some of these tweets. What do you think they mean? This might be totally different from what someone else thinks they mean! See what I’m saying? That’s what makes this work so interesting-thinking about the ways in which we construct meaning individually and then stepping back and trying to think about it from others’ perspectives. Not only are you coming in contact with others’ thoughts, sentiments, and attitudes. You are also bringing a little bit of yourself to it every time, and so, while it’s important to be thoughtful and to establish some criteria for what things mean, based on what is known, you are a person, and no one knows how to understand people than…well…other people! So, I feel honored to be able to bring concreteness and some scientific realness to the things that we express about our experiences.