Sentiment Analysis using R
Meetup Description
After months of postponements and re-appointments, the meetup came to fruition a talk on Sentiment Analysis using different R packages. The meetup aimed at looking at positive and negative sentiments in texts, but also more detailed emotions such as surprise or fear. We learned how to visualise commonly used positive and negative words. The session was suitable for all levels and didn’t need any previous experience with this topic.
Sentiment Analysis
Sentiment analysis (also referred to as subjectivity analysis or opinion mining or emotion artificial intelligence) is a NLP technique that identifies important patterns of information and features from a large text corpus.
● It analyzes thought, attitude, views, opinions, beliefs, comments, requests, questions, and preferences expressed by an author based on emotion rather than a reason in the form of text towards entities like services, issues, individuals, products, events, topics, organizations, and their attributes
● It finds the author’s overall emotion for a text where text can be blog posts, product reviews, online forums, speech, database sources, social media data, and documents.
Exercise
Use Animal Crossing Data and perform sentiment analysis using either PART-2
Animal Crossing is a 2020 “sandbox” game, where your character lives on an island with a variety of different animal characters and collects resources to progress and upgrade the island. It has had mixed reviews: either it is the best game ever, or boring and pointless. It has also been criticized for the fact that you can only have one save game per console (“forcing” families/couples to buy extra consoles to avoid fights over island decor..)
“user_reviews” includes the date of a review posting, the user_name of the writer, the grade they give the game (0-10), and the text they wrote.
user_reviews <- readr::read_tsv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-05-05/user_reviews.tsv') #download from tidytuesday github head(user_reviews)Resources
Workshop repository: https://github.com/manika-lamba/rladi…
This book focuses on a basic theoretical framework dealing with the problems, solutions, and applications of text mining and its various facets in a very practical form of case studies, use cases, and stories.
Tidy data with Sentiment Analysis
Amazon: https://www.amazon.co.uk/Text-Mining-…
Springer: https://link.springer.com/book/10.100…
Book Website: https://textmining-infopros.github.io…
Github Account of the book: https://github.com/textmining-infopros
About the Speaker
At the time, Manika Lamba was a 4th-year Ph.D. candidate in Library and Information Science at University of Delhi, India. She completed her MPhil and Master’s degrees in Library and Information Science from the same department. She also holds degrees in MSc Plant Biotechnology and BSc(H) Biochemistry. Her research focuses on information retrieval, digital libraries, social informatics, and scholarly communication using text mining, natural language processing, and machine learning techniques.
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