Interview with PRIMA grantee Anne-Sophie Bories

Anne-Sophie, first of all, congratulations on your PRIMA Grant. Could you please explain briefly the aims of your research project?

The project is about the interaction of two phenomena: One is versification, which examines regularities and irregularities in length, rhymes and rhythmic aspects in poems. Verse forms come with meanings, and studying versification offers a deep view into the poems, and offers opportunities for text interpretation. The other phenomenon is humor. Even though these are two very different subjects, they have various features in common: Humor and versification both step aside from a genuine communication and both require a high degree of control over the moment, rhythm, contextual and intertextual complexities. They both exploit the effects of the unexpected and rely on the creation of a habituation for the reader: A joke’s punchline works like a switch, revealing a hidden scenario, which we suddenly realize had been there right from the beginning. Poems often work in a similar way: first, you only recognize the evident meaning, but when looking closer you discover a second or even third level, which may not be compatible with one another.

This project aims to acquire a precise understanding of the roles of humor in poetry, and to allocate the forms of versified humor in a historical and cultural perspective. How is versification used to produce or increase comedy? What are the consequences of using verse in a humorous text? I want to examine the richness and variety of practices and results behind this association.

My methodology is based on acombination of distant reading, through text search and data analysis, and close reading. I apply different filters on my digital corpora to identify, isolate or prove stylistic elements that would have gone unnoticed or remained at the intuition stage without the digital tool. Once I have my data I conduct a number of analyses to test the hypotheses and intuitions I have about texts. This is an exciting part, because the data may show something else, something I had not thought of. This is very enriching, because I can then go back to the text, to a very close, traditional reading, and I am then able to examine findings that would not have occurred to me, just from the natural reading. Through this multifocal view combining computational and traditional methods, I can see minute features over a massive corpus of several million words at once. This dialogue between my human mind and the machine is the core of my working method.
 

PRIMA is a very competitive funding scheme, which is evaluated in two steps. Can you tell us what the biggest challenges were in both phases? Is there anything the review panel was particularly focused on? How did you prepare for the interview?

The first phase, the writing of the project itself, was the most challenging. I needed to plan in advance, have a good idea and to present it as efficiently as possible. I had to do a lot of research on humor, for, although I have worked a little bit on this before, so far, I am not a specialist of humor. To build a project that was coherent and feasible, I had to decide which tools to use, which skills to gather and what staff to hire. Then after an intense writing phase, the proposal was too long and needed to be condensed; that, too, was an interesting challenge.

The second part, preparing for the interview, is more fun, it is about reaching out to the audience in an immediate way. It is very important to tell an engaging story when you have just ten minutes to present a five years’ project. The interview training, which the Career Advancement Office has organized, was invaluable. My colleagues came, made comments, and asked me questions that then came up in the actual interview. It has also prepared me for the more standard questions, not just those related to the topic. In addition, the interview training forces you to prepare well ahead of time, leaving ample time to improve the presentation afterwards. One question from the panel was about my position, as a possible future professor, on issues of interoperability in Digital Humanities (DH). That was a very relevant question as currently researchers explore different directions and many new methods used are not compatible.

Why did you chose to come to the University of Basel?

Because of Professor Hugues Marchal, who is the chair of modern French literature at the Department of Languages and Literatures. I already knew his work and admired him as a scientist, which is why I approached him with my initial project a few years ago. I have been welcomed in the best possible way. Having worked with him on that initial project, I found  him to be an excellent mentor. Part of why I am so happy to have this fellowship is that I can stay longer with him here in Basel, this is ideal for me. Moreover, Basel has the Digital Humanities Lab, and parts of the national project NIE-INE (National Infrastructure for Editions) are physically located here in Basel. They are both very competent groups and it is excellent for me to be able to discuss and collaborate with them; I collaborate with NIE-INE to develop web ontologies for the data handling.

Do you collaborate with DH labs in France?

Yes, I am an associate member of the ATILF (Analyse et Traitement Informatique de la Langue Française) lab, which is historically a very important laboratory in France. ATILF built Frantext, the first massive textual database in French, which is well tagged and used to feed “the” French dictionary, Le Trésor de la Langue Française informatisé (TLFi). I am very proud to be part of the ATILF team where I work with Véronique Montémont and Bertrand Gaiffe, and have learned a lot from that collaboration. In addition, I collaborate with the CRISCO (Centre de Recherches Inter-langues sur la Signification en COntexte), where Éliane Delente and Richard Renault run the Malherbe program to analyze verse automatically and precisely. It is brilliant that nowadays, there are enough tools, data and skills in our community, which we can share and make interoperable in order to collaborate.

When have you been introduced to DH methods?

I started using such methods during my master studies. Not because I was encouraged to, but because my investigations required the use of databases and statistical analysis. I always had more needs and had to learn new programming methods in order to reach my goals. It has been a very rewarding experience for me. Along the way, I have been able to reach goals that are more ambitious and to ask questions I would not have been able to answer without these skills. In the meantime, I have myself founded a group called “Plotting Poetry”, a network of researchers working on poetry with computational methods. We organize a conference every year and this is an opportunity to start collaborations and to discover, what other teams are doing in the field.

Do you think the increased use of computational methods in social sciences and humanities (SSH) renders these research fields more attractive to younger generation of students, e.g. by making it possible to develop apps and software?

Progressively, we are going in this direction, where students will be able to make use of tools borrowed from natural sciences within their SSH initial training. I do not know if this makes it more attractive to students, because people, who are primarily interested in computer science, will study computer science and not French literature. But for those, who are hesitating whether to study natural sciences or SSH, being able to apply methods from the natural science’s culture in SSH could be a win-win situation. It is a steep learning curve, however, and it is better to climb it during the initial training than later on. I expect that, as more digital humanists are hired as professors, this training will be offered more often to students as part of their initial training.

Do you see limits and hazards in the computational analysis of language and texts?

There is a danger with computational analysis, and it is linked to the resistance of the material. It is difficult to collect good quality data. We try to make it as automatic as possible, because collecting data manually is extraordinarily time consuming, frustrating, not to mention difficult as you need to set your common sense aside. Having the machine do it poses a whole new set of issues, it is yet another process. Therefore, because this is such a difficult task, there is always the danger that data collection will take the lead, will become the aim. Researchers are collecting more and more data of increasing quality, but then you have to do something with it, and there is always a risk to see your hermeneutic goals pushed further and further away. One needs to keep in mind that the machine is but a means: the aim of a project should always be to get good interpretative results and not to drown in the technical data collecting effort. This is why I am so excited that in this project I have an IT programmer. This will improve my productivity incredibly and will allow me to spend more time interpreting the data.

How is the development of Digital Humanities and Digital Humanists today?

There are many digital humanities labs or departments sprouting at universities, including here in Basel, and this is a very good thing. I also think that individual departments should and will build up their own programming skills, and include them within the initial curricula. This will foster a new generation of true digital humanists, capable of choosing and using tools from both traditional scholarship and novel methods, and it will also equip our students not headed towards research with competences they need on today’s job market.  In many groups, computer scientists and literary scholars work together, and we are seeing the emergence of researchers with both sets of skills, which is very enriching for us literary scholars. People with this kind of interdisciplinary profile securing professorships, will encourage such inclusion, and boost the current transition towards a greater methodological diversity.

Thank you very much for this interview, Anne-Sophie. We wish you every success for your PRIMA project and your future career.

Thank you for inviting me.