When I set out to do sentiment and toxicity analysis of Canada’s Question Period sessions, I held out hope that all the number crunching would reveal some hidden insight into Canadian politics. Perhaps something lurking a bit below the surface that only a bit of Python, a few APIs and TextBlob could reveal.
Sadly that hasn’t happened but the whole exercise has revealed a few things that surprised me.
Continue reading “Which is the most negative political Party? What does sentiment analysis tell us?”
This past winter I was teaching a class on Social Networks at George Brown College and we examined how many companies are using social media sentiment analysis to get further insight on the public’s perception of their brand and products.
We went through a few great examples of how computer generated sentiment analysis was being used in a variety of fields including journalism. Vox’s article from 2016, where they did sentiment analysis on seven months of Donald Trump’s tweets, inspired me to move beyond abstract discussions about sentiment analysis and figure it out for myself.
Continue reading “Sentiment analysis on Question Period speeches using TextBlob, the Perspective API and Python”