mswulbers / big-tech-attitudes

Code associated with the paper "Fantastic Four or Uncanny Collective? The Public’s Evaluation of Big Tech Companies in the Times of an alleged ‘Techlash’"

Big-Tech-Attitudes

Code associated with the MSc Dissertation "Fantastic Four or Uncanny Collective? The Public’s Evaluation of Big Tech Companies in the Times of an alleged ‘Techlash’ ".

Content

1. VADER Sentiment Analysis

I use the VADER sentiment lexicon (Hutto & Gilbert, 2014) to perform sentiment analysis on textual Reddit data. This serves to analyse public sentiment towards Google, Amazon, Facebook and Apple during 2018, when the Cambridge Analytica scandal was revealed.

2. Tf-Idf Word Frequencies

Word frequency analysis is conducted using tf-idf to extract keywords from Reddit comments.

3. Word2Vec Word Embeddings

Using Word2Vec (Mikolov et al., 2013), word embeddings are leveraged to assess semantic relationships between the terms 'Google', 'Amazon', 'Facebook', 'Apple' and ‘Cambridge Analytica'.

References

Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.

Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. In Proceedings of workshop at ICLR.