Born and raised in Brazil, Luana moved to The Netherlands in 2017 and obtained her Master's degree in New Media & Digital Culture at Utrecht University in 2018.
Fascinated by the interplay between business and technology and with a strong interest in data science, Luana is a self-taught programmer. As a student at Utrecht University, she hosted a weekly data clinic assisting BA and MA students by tutoring them on digital methods and tools such as R, Tableau, and Gephi.
After graduating, Luana worked as a Data Scientist. Her responsibilities included researching and training Natural Language Processing models and developing machine learning algorithms for Named Entity Recognition and Text Classification. She was also part of the team responsible for implementing the algorithms in state-of-art business web platforms using a Python-based web development framework (Django).
Since 2019, Luana has worked at the Utrecht University of Applied Sciences, at the Creative Business program. She teaches various research and technology-focused courses. She is also a graduation supervisor, coaching students during their graduation process, and a work placement supervisor, supporting and supervising third-year students doing internships.
Fields of expertise
- Data Visualization
- Critical Technology
- Research methods
- Student Supervision
Luana investigated Twitter discourses and the Brazilian online media ecosystem. She focused on computational propaganda on Brazilian Twitter, describing how political movements used automated accounts to influence the Brazilian political agenda.
|Project title||Narrative Wars: How Brazilian Twitter users framed online news articles following nationally polarizing political events|
|Keywords||Brazilian online media ecosystem, protest hashtags, networked framing theory, digital methods, political bots, disinformation|
|Years of completion||2018|
|General project description||This study explores the Brazilian online media ecosystem and Twitter discourses around former president Luís Inácio Lula da Silva and the corruption charges against him in 2018. Public tweets were collected and analysed using a mixed-method approach, resulting in two separated but connected maps: a retweet and a domain network of the hyperlinks shared. These graphs were qualitatively examined in the light of networked framing theory. It was found that the Brazilian political debate on Twitter was highly polarized, contaminated with conspiracy theories, and heavily influenced by dubious news outlets. News items were intertwined with conspiracy theories, propaganda, and false news. This work also reveals that even though the opposing groups were structurally different, they shared ideological similarities and manifested a widespread distrust of mainstream media.|
|Your Role in project||Primary researcher|
- MA New Media & Digital Culture, Utrecht University (2018)
- BA Communication and Media Studies, CEUT (2017)
- Data Ethics, AI and Responsible Innovation, EdinburghX (University of Edinburgh) (2021)
- Basiskwalificatie Didaktische Bekwaamheid, HU (2020)
- Data Visualization with Tableau, University of California, Davis on Coursera (2020)
- Advanced NLP with spaCy, DataCamp (2019)
- Supervised Learning with scikit-learn, DataCamp (2018)
- Natural Language Processing Fundamentals in Python, DataCamp (2018)