Mª Luz Congosto
Mariluz Congosto is a PhD in Telematics from the Carlos III University and a degree in Computer Science from the Polytechnic University of Madrid. Since 2008 she is a researcher at the Carlos III University, specialized in the analysis of social data, preferably on Twitter. She uses network analysis and visualization to discover patterns of behavior, message propagation and user characterization. For her experiments, she has created the t-hoarder platform that allows monitoring the evolution of events on Twitter in the long term. With this tool, she has built a social barometer with the reactions of citizens before political scandals and Metro faults that analyzes the perception of the quality of the Madrid metro through the messages of the users of this service. She has been an associate professor for two years at the Polytechnic University of Madrid and four years at the Carlos III University. For 20 years, she has worked in large innovation projects in the telecommunications environment for the Telefónica operator (TESYS, MORE, EOC, …). From 2000 to 2008, she worked in the diffusion of technology and collaborated with Fundación Telefónica creating platforms for digital publications.
Interview to Mª Luz Congosto (Researcher at Universidad Carlos III de Madrid):
Q: What led you to dedicate yourself to research in your area of expertise? Was it related to what you were doing before?
A: It took me the completion of a Master and a Doctorate. It was not related to my work but the accumulated experience helped me a lot to work in this field. I had to learn many new things but the programming part was very simple.
Q: Speaking of your work… What is a typical day like? Do you research alone or in the company of others, and if so, next to what kind of academic profiles do you work or would you like to work?
A: My research is very interdisciplinary, I have written articles with engineers, with journalists, with sociologists and with political scientists. There are topics that I look for and others that come to me through collaborations.
Q: If you had to explain to an internet professional the progress of your research and how you can take advantage of it for your marketing strategy… How would you do it?
A: Trying to convince you of the importance of incorporating network analysis into your reports. It is a science that can have a lot of potential for marketing and there are free tools that help carry out these studies.
Q: What is the biggest difficulty you find in relation to the data providers on the Internet (Twitter, Facebook, etc.)? For example, the variety of APIs, the prices, the changing coverage (with which the universe of your data changes), the opacity of how they obtain them or how they elaborate certain indicators, other problems…
A: I basically work with the Twitter API and for now with the free option. The rules or the interface change from time to time and you have to adapt. Now to have an app to download data you have to register as a developer and it is a slow process. The part of obtaining payment data from the API is not very clear, before it was done by genip, a Twitter company, but now there is a new API to download payment data and I have not seen prices anywhere.
Q: From your point of view… What would you say is the most important indicator or data? (killer data) if there is.
A: All the data is important and many times the value is in combining them.
Q: This is a recurring question in our interviews: In the medium term, do you think robotization will come to dominate your area of knowledge or will there always be a human value that guarantees the survival of human professionals and researchers?
A: I think it will help to make things faster in my research but the part of the initial question will remain in the hands of human researchers.
Q: We have mentioned your scientific research before… Could you tell us a preview of this one, something that you are investigating and that will come to light soon?
A: I’m investigating the noise on Twitter trying to identify false profiles by their behavior and by the propagations. I also have another way of analyzing the behavior of suspended profiles.