Text Analytics And Natural Language Processing

1099 Words Jan 20th, 2016 5 Pages
A. The Sentiment analysis process
i) Collection of data ii) Preparation of the text iii) Detecting the sentiments iv) Classifying the sentiment
v) Output

i) Collection of data: the first step in sentiment analysis involves collection of data from user. These data are disorganized, expressed in different ways by using different vocabularies, slangs, context of writing etc. Manual analysis is almost impossible. Therefore, text analytics and natural language processing are used to extract and classify[11].

ii) Preparation of the text : This step involves cleaning of the extracted data before analyzing it. Here non-textual and irrelevant content for the analysis are identified and discarded

iii) Detecting the sentiments: All the extracted sentences of the views and opinions are studied. From this sentences with subjective expressions which involves opinions, beliefs and view are retained back whereas sentences with objective communication i.e facts, factual information are discarded

iv) Classifying the sentiment: Here, subjective sentences are classified as positive, negative, or good, bad or like, dislike[1]

v) Output: The main objective of sentiment analysis is to convert unstructured text into meaningful data. When the analysis is finished, the text results are displayed on graphs in the form of pie chart, bar chart and line graphs. Also time can be analyzed and can be graphically displayed constructing a sentiment time line with the chosen…
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