Tools and Guides

Tools used in this workshop

• Anaconda: https://www.anaconda.com/products/individual
• VADER (Valence Aware Dictionary and sEntiment Reasoner): https://pypi.org/project/vaderSentiment/
• NLTK (Natural Language Toolkit): https://www.nltk.org/

Sentiment Analysis

Guides and Handbooks

• Cambria, Erik, Dipankar Das, Sivaji Bandyopadhyay, and Antonio Feraco. A practical guide to sentiment analysis. Springer, 2017.
  UBC Library link (ebook available): http://resolve.library.ubc.ca/cgi-bin/catsearch?bid=8790457

• Liu, Bing. Sentiment Analysis: Mining Opinions, Sentiments, and Emotions. 2nd ed., Cambridge University Press, 2020. UBC Library link (ebook available): http://resolve.library.ubc.ca/cgi-bin/catsearch?bid=11466845

• Thelwall, Mike. “Sentiment Analysis.” The SAGE Handbook of social media research methods, edited by Luke Sloan and Anabel Quan-Haase, SAGE Publications Ltd, 2017, pp 545-554. UBC Library link (ebook available): http://resolve.library.ubc.ca/cgi-bin/catsearch?bid=9081741

• Thelwall, Mike. “Sentiment analysis for small and big data.” The SAGE Handbook of online research methods, edited by Nigel G. Fielding, Raymond M. Lee and Grant Blank. SAGE Publications Ltd, 2017, pp. 344-360. UBC Library link (ebook available): http://resolve.library.ubc.ca/cgi-bin/catsearch?bid=8980976

VADER (Valence Aware Dictionary and sEntiment Reasoner)

• Hutto, C.J. & Eric Gilbert, E.E. “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. https://www.aaai.org/ocs/index.php/ICWSM/ICWSM14/paper/viewPaper/8109

Multilingual Sentiment Analysis

• Dashtipour, Kia, et al. “Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques.” Cognitive Computation, vol. 8, no. 4, 2016, pp. 757-771. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4981629/

Sample Sentiment Analysis Projects

NaSent – Stanford’s Neural Analysis of Sentiment Analyzes sentences from movie reviews and gauges the sentiments they express on a five-point scale from strong like to strong dislike. Experiment with the online demo at https://nlp.stanford.edu/sentiment/