Sentiment Analysis Report: Using R Software for Market Analysis

This report provides a comprehensive overview of sentiment analysis, focusing on its application using R software. It details the process of text mining, which involves extracting data from online sources like social media, and explains the use of the polarity test algorithm to categorize sentiments as positive or negative. The report highlights the importance of sentiment analysis in understanding customer opinions and its various business applications, including marketing strategies, product development, and customer service improvements. Ultimately, it underscores how sentiment analysis can lead to increased sales, revenues, and profits. The report also includes relevant references to support the analysis.

SENTIMENTAL ANALYSIS
SENTIMENTAL ANALYSIS
Sentimental analysis refers to a technique in statistical analysis that is used when the aim of a
research is in determining the nature of the opinion of an individual on the subject of the study
(Apoorv, et al., 2011). In the R Software, sentimental analysis is carried out by first applying text
mining and then proceeding on to run the sentimental analysis algorithms. Text mining is a
technique for data mining that obtains data in form of texts from sources such as online platforms
(Badal & Kundrotas, 2015).
One of the sentimental analysis algorithm is the polarity test sentimental analysis which
categorizes a statement as either positive or negative. The polarity test sentimental analysis finds
application in determining the popularity of products that have been newly introduced into the
market. Here, data is collected through text mining from the comments on a social media post
about the product. Once the R software carries out the text mining and stores the comments as
text-document matrices, the polarity test algorithm then classifies each of the comments as either
positive or negative.
The main benefit of conducting a sentimental analysis is the ability to obtain a more detailed
understanding of the opinion of an individual beyond the face value. In terms of business,
sentimental analysis is critical in development of marketing strategies, product development,
crisis management and improving of the customer service. All the above benefits of sentimental
analysis in terms of business cumulatively results in the increase in sales, revenues and profits.
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SENTIMENTAL ANALYSIS
REFERENCES
Apoorv, A, Xie, B, Rambow, O & Passonneau, RJ 2011, Sentimental Analysis of Twitter Data,
Columbia University, New York.
Badal, VD. & Kundrotas, PJ 2015, 'Text Mining for Protein Docking', PLoS Computational
Biology , vol.11, no.12, pp. 1-5.
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