Python Project Sentiment Analysis and Information Extraction

In this quick projects overview, we go through two projects in python using Spider.

Project 1: Reading data from the dataset, preprocessing, and structuring it. Then training a classifier on it. When a user gives any review at runtime, it processes it and the trained model predicts where the review is positive or negative. Next, it also suggests the related documents to the submitted review.
Project 2: It reads unsupervised data and uses topic modeling to identify key features from the data, being a dimensionality reduction technique. Each feature represents the aspect of the commercial products provided as input data. Topic modeling is also used as an information extraction technique as it extracts useful information as topics from a huge collection of documents. The topics can be considered as the subjects discussed in the data. Next, we perform sentiment analysis on each subject. For any given data it will help to identify what people are discussing and whether they are having positive or negative sentiments based on public review. It can also be considered aspect-based sentiment analysis. #textminingproject #projectoverview #nlpproject #nlp #naturallanguageprocessing #textmining

[DnyaneshwarPanchaldsp]

this program showing an error in senti_synset =
IndexError: list index out of range