About

I am a digital practitioner and social media researcher. Currently I lead the digital team at the Vaccine Confidence Project at the London School of Hygiene and Tropical Medicine where I analyse data generated through media monitoring and local media signals in immunisation programmes and public sentiment around COVID-19 in countries worldwide.

***My latest publications: Impact of COVID-19 vaccine misinformation and Assessing COVID19 Vaccine Hesitancy

My interests include Social Media, Misinformation Narratives, Social Network Analysis, Strategic Communication and Information Politics. More specifically I specialise in Social Listening, Fake News, Misinformation and Disinformation narratives, OSINT and SOCMINT. I am also interested in Research Methods and Research Design, Big Data Analysis, Digital Media, Digital Methods as well as Digital Strategy and Digital Transformation,.

I graduated from Kingston University with a BA in Media and Cultural Studies in 2010. Then I spent four years travelling in Asia and that’s where I got heavily involved in social media, especially hashtagging and trending topics analysis on Instagram and Twitter, which eventually resulted in my academic interest in hashtags. In 2014 I completed Masters Degree in Social Research at Goldsmiths College, University of London. In my dissertation, I analysed European cities hashtags rankings on social media. In 2020 I completed my PhD in social media analysis focusing on misinformation and agenda setting on Twitter at the Centre for Interdisciplinary Methodologies at Warwick University supervised by Celia Lury and Rob Procter. During my time at Warwick, I coined the terms Hashtagability and Algorithmic Ownership.

Publications

Lecturing and Teaching

  • Spring and Autumn 2018 – Practice and Interpretation of Quantitative Research (2nd Year Undergrad level) University of Warwick, UK. This is a Year 2 core module which covers elementary quantitative methods skills. The aim of the module is to introduce students to the use of quantitative methods for sociologically relevant research. By the end of this module, students are able to critically engage with published quantitative sociological research and undertake elementary quantitative data analysis independently. Students are introduced to the use of statistical software (SPSS) for the analysis of large-scale quantitative data. The module builds on research design skills acquired in other modules and aims to develop practical research skills related to quantitative methods.
  • Spring 2017 – Modelling Social Data II (MA, PhD level), Goldsmiths College, University of London, UK. The course covers multivariate modelling involving the advanced statistical techniques. Areas covered:
    • the principles of regression analysis, multiple regression analysis and path analysis
    • the core features of data reduction and scaling techniques such as multiple indicator scaling, regression weighted scaling, cluster analysis and factor analysis
    • the full range of statistical and modelling assumptions made in the conduct of regression analysis and how the consequences of making these assumptions may be assessed and if necessary responded to.
  • Spring 2017 – Researching Society & Culture (1st Year Undergrad level), Goldsmiths College, University of London, UK. This module is lecture and workshop based and aims to introduce students to the methods that sociologists have developed to analyse their societies and to produce sociological knowledge. Students are encouraged to develop core skills in methods of research by being introduced to the practice of sociological research. Methods are introduced in relation to key sociological topics and research traditions that are closely identified with them, thus allowing students to confront methods as real practices rather than abstractions. The course also covers: Introduction to Quantitative Sociology, Introduction to SPSS, Univariate and Bivariate Data Analysis Using SPSS
  • Spring 2017 Introduction to SPSS (3rd Year Undergrad level), Goldsmiths College, University of London, UK. The aim of this module was to introduce students to Quantitative Sociology and especially Univariate, Bivariate and Multivariate Data Analysis Using SPSS
  • Autumn 2016 – Modelling Social Data I (MA, PhD level), Goldsmiths College, University of London, UK – This module provides advanced level training in theoretically informed quantitative social research, proving skills in using contemporary software programmes (SPSS) and enabling the exploratory secondary analysis of large data sets. The module introduces the methods and procedures of quantitative social research, including the formulation of research questions, use of previous research findings, the role of models and model building, operationalisation of concepts and study design. The module covers both analytic (causal inference) and inferential statistics confidence intervals and significance tests) and these are applied in social survey data analysis
  • Spring 2016 – Understanding Social Research (1st Year Undergrad level), University of Warwick, UK -The aim of the module is to develop critical thinking about empirical social research and to introduce students to a wide range of studies which apply quantitative and qualitative methods. Understanding Social Research module provided a firm foundation on principles of research design and social research methods.
  • Spring 2015 – Understanding Social Research (1st Year Undergrad level), University of Warwick, UK – The aim of the module is to develop critical thinking about empirical social research and to introduce students to a wide range of studies which apply quantitative and qualitative methods. Understanding Social Research module provided a firm foundation on principles of research design and social research methods.