Sentiment analysis using Twitter data
Organised by Sophie Meakin
Abstract
Sentiment analysis uses natural language processing (NLP) to identify and quantify an individuals opinion on a topic. Twitter is one example of where individuals express their opinions about many different subjects. My proposed project is to collect data on a certain topic and then analyse the content, for example:
(1) PhD sentiment analysis: The #PhDChat hashtag was originally created as a way for PhD students in the UK to hold weekly discussions, but it has grown into much more than that and is now used by PhD students and others around the world to talk about the challenges and successes of studying for a PhD, ask for advice, and provide support. We can collect tweets containing the #PhDChat hashtag and analyse the tweets using Python libraries for natural language processing/ sentiment analysis.
(2) We could collect data on anything, suggestions are very welcome! For example:
- Tweets from Donald Trump: https://dev.to/rodolfoferro/sentiment-analysis-on-trumpss-tweets-using-python-
- Brexit: http://bruegel.org/2016/11/tweeting-brexit-narrative-building-and-sentiment-analysis/
Aims and Objectives
(1) To understand the sentiment of Twitter users using the #PhDChat hashtag.
Of Interest to
Anyone interested in natural language processing, novel uses of social media data, or anyone who has ever wondered how much other people are enjoying their PhDs.
Resources Necessary
Data will be collected and made available before the retreat. Updates on other resources required to follow.
References
The Structure and Characteristics of #PhDChat, an Emergent Online Social Network: https://www.youtube.com/watch?v=64uSxFeeV5s