Sentiment Analysis, Big Data, and Policy

Most of my work so far has been in qualitative methodologies, but as I progress through my Web Analytics course, I find that Big Data sparks my interest like RCTs and other quantitative methodologies never have. I am also focusing on Social Media and learning in a research project that I am a part of and plan to engage with it in my dissertation from a policy standpoint.

As I read the Batrinca & Treleaven (2015) article for my web analytics class, I started to wonder how text analytics and sentiment analysis might be used to gather more information regarding how people felt and talked about policy. Twitter and other platforms are all used to discuss policies and programs that have passed, what outcomes they have produced, and people’s feelings about all those aspects. I wonder how Big Data might be used to provide more background and be used to make decisions regarding policy and amendments to those policies and if there is a way to use the processes to collect qualitative data as well. Is it possible to locate what was said by those that felt alienated from a policy for example, and use this qualitatively to aid in evaluation, decision making, and future planning?

Batrinca B., & Treleaven, P. C. (2015). Social media analytics: A survey of techniques, tools and platforms. AI & Society, 30, 89-116. doi: 10.1007/s00146-014-0549-4

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