Alankrita Malhotra is a sophmore and is forging an interdisciplinary path by combining her passions for Data Science and the humanities. Her work on computational folklore and Nordic flavor networks under the guidance of Professor Timothy Tangherlini, who we interviewed for the project last month, highlights the innovative potential of digital humanities. In this interview, Alankrita shares how her academic journey bridges STEM and the arts, the challenges and rewards of interdisciplinary study, and the profound connections she’s discovered between history, culture, and technology.
What is your major, and what are your main academic interests?
My name is Alankrita Malhotra. I am currently a sophomore. I’m planning to double major in Data Science and English, or Data Science and Economics with a minor in English. I’m someone who gets a lot of looks when I say that I’m a Data Science and English major, because people assume those two things don’t go very well together. I think what’s fascinating is that in college I found something called the digital humanities, which marries those two interests together. Professor Tangherlini, the professor who is heading this project, is actually the head of the digital humanities group, and works on cultural analytics. Coincidentally, that’s one of my main areas of interest! I also really like quirky stuff like computational folklore, which Dr. Tangherlini also does.
Can you describe the research project you are working on for Professor Tangherlini? How did you get involved in this project?
For context, I am an international student from India. Where I studied growing up, I was always told to choose between the humanities and the sciences, so I never had the chance to do both. That’s why I wanted to come to Berkeley to study. When I got here, I decided to take the most wide-ranging course load possible. My first semester, I was taking Math, Sociology, Data Science, and English. I found my sociology class fascinating, and I went to talk to my professor in office hours. I told him that I’m really interested in folklore, and was seeing lots of connections between sociology, folklore, and English. He told me to be careful, because he’s writing a book on folklore. And he told me that, as a Data Science major, I should know about computational folklore and that a person who’s really good at it is at Berkeley. I had never heard those two words put together before, so I was intrigued. He told me to go talk to Professor Timothy Tangherlini. I went to his office one day, and I said, “I really want to do computational folklore. Can you let me research with you?” He was quite taken aback, especially because I was a freshman. I just kept showing up and emailing him, and at the end he told me that he has an interesting project on Nordic flavor networks. And that’s how it started. So it was quite by chance, but I think it ended up being one of the coolest things I’ve done.
It’s fascinating, because every time I say those three words – Nordic flavor networks – people get confused, so I end up dissecting each word separately to explain it. So, Nordic: We’re looking at Scandinavian countries, and we’re looking at historical cookbooks from the 16th century onwards. We’re emailing and getting resources. We’re getting old cookbooks from libraries, from online resources, and then we’re using a data pipeline to get those cookbooks into a form where we can map them onto a bipartite network. We first translate them from whichever dialects they are in into English, and then we have to break apart each recipe, because every cookbook looks different in a PDF. We extract the recipes – we extract the names, ingredients, and methods used in that recipe. We do this because the methods inevitably change how the ingredients taste. For example, if I heat butter and fish, it’ll have different chemical compounds than the individual chemical compounds in butter and fish. We get everything and map it onto a bipartite network. We’re doing that to understand flavor pairing.
Flavor pairing is also very interesting. So for example, in the Western world, we often pair wine and cheese: that’s a very popular combination. Other examples are bacon and eggs, or chocolate and coffee. A lot of the time, these really popular pairings come from the fact that these two things share very similar compounds: they have certain lipids or certain acids that are common. The Western world tends to pair them. But when you look at the Eastern world – if you look at Indian cuisine, or Thai food – you’d see this combination of ingredients that have very different flavor compounds. You have soups that have sweet and tangy, or whatnot. This process of flavor pairing changes depending on the region you look at. I think when Tim was interviewed about this, he talked about Yong-Yeol Anne’s work. That’s fascinating, especially coming from an Indian household, it’s interesting to look at Scandinavia as an analog profile, from this lens of getting these ingredients and looking at flavor, even though it’s subjective.
Can you speak a bit more about the subjectivity of taste in this project? What kinds of barriers has that caused, and what solutions have you all come up with?
It’s interesting, because I actually don’t know how to cook. I’m learning a lot about the process. We have to be objective in some way, so what we’re doing is using flavor as a proxy for taste. Taste is subjective, but flavor isn’t, because flavor is given to something by the combination of its chemical compounds. You know that these two things combined together generally give a bitter flavor, for example. Because we cannot completely quantify what something tastes like – and that changes because of taste buds or personal opinions – we’re looking at chemical reactions instead.
Another thing we’re having to substitute for is that we’re assuming these books represent what people are actually eating. That is also a jump. The way we’re trying to combat this is by looking at people’s cookbooks. Because another interesting thing is that cooking in these Scandinavian countries was something that was very elitist, initially. These cookbooks were written by personal chefs, and used by other personal chefs. There was a period of time where this slowly started shifting to where cookbooks were being written for the people from the people, like Froken Jensen. Jensen wrote a famous, very comprehensive cookbook, and it’s one of the first ones we picked up, because it’s for the people by the people – it does represent what recipes were being created during that period. We were going to try to do this across centuries, and across these different Scandinavian countries, so that we can understand what flavors are coming out of where. Are new spices being introduced? Are new flavors being introduced? Does that coincide with a new trade embargo that was started between two countries? It becomes a lot more about the history, the politics, the global market, just as much as it does about chemical compounds and reactions.
Can you speak more about your interdisciplinary approach, being involved both in STEM and the humanities? What advice do you have for undergraduates who might be timid to try it, and what have you learned from your approach?
I think it’s the best thing ever. I think being in this position where you’re in both kinds of classrooms, situates you very uniquely on the map of trying to learn something new. When I’m in my English classes, I’m sitting at a desk surrounded by 20 other students, and we’re discussing the intricacies of poetry, we’re discussing Langston Hughes, we’re discussing individual poems and spending an hour and a half on one page. And then I go into my Data Science classes, and it’s 1,800 people learning about whatever new algorithm we’re learning that day. They both expose you to different ways of understanding the world. I came in as an English major, not completely sure I’d do Data Science. What I realized was that a lot of the problems I wanted to solve in the world – accessible education, equitable access to resources – I faced a problem when trying to scale them. For example, folklore: there are a lot of interesting parallels I found, for instance between Jatayu, who is this vulture in Indian mythology, and Icarus and Daedalus, from Greek mythology. They’re very similar stories. I was finding these really cool parallels, but I didn’t know how to systematically study them across history and culture until computational folklore. Computational folklore allows me to take all of the data and synthesize it, and understand that sphere a lot better.
It’s definitely difficult though, because sometimes in my English classes I don’t feel English enough and in my Data Science classes I don’t feel techy enough. There is that balance of the two worlds.
What would my advice be? When I came to Berkeley, I was sitting for a Data Science talk given by Professor Ani Adikari, and she said, “College is the last time that you will sit in a classroom, and someone who knows everything there is to know about a subject will tell everything they know.” I think that’s really stayed with me, because I want to take classes in every department before I graduate. If you’re the kind of person who knows exactly what you want to do, that’s really great. But if you don’t, I would say to embrace it. Take classes across the board – not just to fulfill your breaths, but to really look through different perspectives while looking at the same thing. You’ll find awesome combinations that you didn’t even know existed, like the digital humanities or computational folklore.
What book have you read during undergrad that you would recommend to everyone reading?
I’ll give one which is very close to my heart – it’s been a favorite of mine for a while – and interestingly, it won’t take you more than 30 minutes to read. It’s something called, “The Hatred of Poetry” by Ben Lerner. I can’t give a gist of a book, but I will explain the motivation behind it, and why it stays with me to this day.
There’s this famous poet, Marianne Moore, and one of the poems she wrote starts with, “I too dislike it.” The entire poem is about poetry itself, and about hating poetry. And this is an established poet who is saying this. So this entire book is about the hatred of poetry, and it too is by a poet. Why I really find this book interesting, and why I want everyone to read it regardless of whether they like poetry, is because I think poetry embodies a very human tendency to always want.
I’ll explain that through a story. The earliest poet that we knew about was a man called Caedmon. He didn’t know how to sing, and he used to go to these feasts, and sometimes they would ask him to sing. He would turn his head away in shame. In one of the feasts, they told him he had to sing, and he refused. He ran away and went to his shed, and cried himself to sleep. In his dream, God came, and said, “Caedmon, open your mouth and sing,” and he said, “But I don’t know how,” but God told him he had to. When he did open his mouth to sing, lovely voices flowed out. He sang about God and it was beautiful, and when he opened his eyes, he still remembered those verses. So the first thing he did was write it down. It was an epic poem, and everyone loved it. He became famous. But he was intensely dissatisfied with it. That is because poetry comes from this place of wanting to convert what’s in your brain – which in your eyes is perfection – into words. As soon as you translate those tongues, you lose out on that perfection. So it’s about striving, and continuing to try to be the best you can be. I think currently in this world, I find that poetry beautifully embodies the spirit of the human nature of constantly wanting more. I think it really opened my eyes as to poetry coming from a place of disdain, and it let me think about myself wanting more, and striving for more. We go to Berkeley: it’s competitive, and we always want to do more. So I would highly suggest, “The Hatred of Poetry.”