Journalist, Data Analyst, Computational Social Scientist, and Founder
-> Check out my CV
Here is what drives me :)
My journey starts at the moment in time when I made what I consider a courageous decision, and decided to take on the challenge to transition from journalist to data journalist. It was during my Bachelor in Journalism in Scotland, as I was trying to map inequality in Scotland using census data, I had started realising that nowadays news organizations can not just benefit, but are increasingly reliant, on the ability to work with data, in its extraction, handling, and presentation. The desire to harness the power of data and better grasp the responsibilities coming with it got me to enrol in an MSc in Computational Social Science at Linköping University, Sweden. At the time of writing, I have recently graduated, and am currently doing an internship at Sheldon Studio, following another internship at DataJournalism.com, both relating to data journalism. In the past 2 years I have learned how to program in R, how to do sound statistical analysis including regression, I delved in the theory and practice of social network analysis, agent-based modelling, dimensionality reduction methods, and web scraping. I have worked with computational text analysis and machine learning in my thesis. At DataJournalism.com, I have had the honor to create, analyse, and present the State of Data Journalism 2021 survey. At Sheldon Studio, I am thoroughly enjoying working on the team's diverse projects, which I won't spoiler now but look forward to add to my portfolio :)
As a computational journalist, my aims are generally three-fold. First, I want to avail of data acquiring and analysis techniques to generate journalistic outputs that rely on news values, and strive for objectivity, through numbers, but also for truth, through informed and transparent methodological choices. Second, I am aware there are stories to be found in the vast online realm, ranging from using digital traces on social media networks to better understand human behaviour, to keeping governments accountable or guiding them, and finally to understanding the effects of architectural choices by big social media companies on individuals’ freedom and, more generally, society. Third, I want to use computational tools to make better sense of the directions newsrooms should take in our digital age. Polarization, loss of trust in news organizations, the development of algorithmic journalism, content virality, abundance of information, and shrinking spans of collective attention, are some of the big challenges and opportunities journalism in the twenty-first century is facing, and the industry requires individuals capable of making sense of these complex phenomena. Journalism, data science, and computational social science will increasingly go hand in hand, and I intend to be at the intersection of these fields.
- Making the case for networked privacy as a new privacy paradigm in online social networks
- Leveraging Peer to Peer Influence: Measuring diffusion of online news media publications
- Ethnic residential segregation in Stockholm before, during, and after the 2015-16 migrant crisis
- Rule it, reap from it? An analysis of countries' economic regulation
- Mapping agricultural vulnerability in the DRC
- Popularity and Peer Influence in a South Wales secondary school
- Positive and negative social influence_testing network topologies on continuous opinion dynamics
- Bowling alone or bowling all in all?
- How does perceived discrimination impact mental health?
- The role of discrimination, prejudice, and stigma in generating racial and ethnical mental health disparities in Sweden