Text Mining and Sentiment Analysis
Brant Deppa
Brant Deppa
Winona
State University
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Unsupervised
Learning (DSCI 415) is a recent addition to the Winona State data science
curriculum. Unsupervised learning is the study of methods where we
are working only with a set of inputs/variables in order to find the structure,
relationships, or differences between them. One of the topics in the DSCI
415 is text mining which is the process of deriving quality information from
text. For example, we might want use customer product reviews to
determine the general attitude towards a product or identify certain features
customers like or do not like. Social media such as Twitter ® can be a
source of interesting text regarding opinions/sentiments about certain issues
or individuals, e.g. a political candidate. In this presentation, we will
be looking at the basics of working with, summarizing, visualizing, and
analyzing text data in R.
Time:
12:00 – 12:50
Day: Wednesday,
January 25
Place: Gildemeister
155
Refreshments served beforehand in Math/Stat Student Lounge (GI135)
