Part $2$ :: Sentiment Analysis

Introduction

Sentiment analysis is a computational technique used to determine the emotional tone behind words. It's crucial for understanding opinions in text, such as social media posts, reviews, and any place where people express their thoughts and feelings. This skill is highly valuable across various domains, from marketing and customer service to public policy and mental health research. By completing this assignment, you'll gain practical experience in extracting and analyzing sentiment from textual data, preparing you for data$-$driven roles in many fields.

Objective

Write a Python command$-$line utility that analyzes the sentiment of lines in a text file. You'll identify whether each line expresses a positive, negative, or neutral sentiment$.$ Additionally, you'll compute the overall sentiment of the document. Your program will output a summary to the console and write a detailed analysis to a CSV file. $($see below, for details on CSV files$)$

Requirements

Command$-$Line Interface: Your script should accept the file path of the text to analyze as the first command$-$line argument and the optional name of a $.$csv file for the second. $.$

Analysis Output:

Console: Display the overall sentiment of the document.

CSV File: For each line $,$ include a row with the sentiment value $($positive$,$ negative, neutral$)$ and the line itself if the user requests a $.$csv file.

Sentiment Analysis Logic: Use lists of positive and negative keywords to determine the sentiment of each line. Consider a line positive if it contains more positive than negative keywords, negative if the opposite is true, and neutral if it has an equal number of positive and negative keywords or none of the keywords.

Case Insensitivity: Ensure that your analysis is case$-$insensitive.

Error Handling: Include try$/$except blocks to handle potential errors, such as file not found.

Detailed Instructions

Reading Input: Your script should take the path of a text file as an input argument from the command line. Read this file to process its content.

Processing Text: Split the text into individual lines. For each line, determine its sentiment based on the presence of keywords. Remember to ignore case when matching keywords.

Outputting Results:

Console: Print the overall sentiment of the document $($positive$,$ negative, neutral$),$ determined by the majority sentiment of all lines.

CSV File: Write a CSV file based on the second command line parameter where each row contains a line and its identified sentiment$.$

Error Handling: Use try$/$except blocks to manage errors, such as issues with file reading or writing. Provide meaningful error messages to help users understand what went wrong.

CSV Files

A CSV $($Comma$-$Separated Values$)$ file is a plain text file that stores tabular data $($numbers and text$)$ in a simple format. Each line in the file corresponds to a row in the table, and within each line, columns are separated by commas. CSV files are widely used for data exchange between different applications, databases, and programming languages due to their simplicity and ease of use. They can be opened and edited with text editors, spreadsheet programs like Microsoft Excel or Google Sheets, and processed by numerous programming languages, including Python.

In this project, the Python csv module is utilized to handle writing the sentiment analysis results to a CSV file. The csv module provides functions to easily read from and write to CSV files, making it a convenient tool for data export and import tasks.

For this assignment, the csv module is used in the following way:

Writing to a CSV File: After analyzing each line in the input text file for sentiment $($positive$,$ negative, or neutral$),$ the results are written to a CSV file named sentiment$\_$analysis$\_$results.csv$.$ This file includes two columns: the first column for the sentiment value of each line and the second column for the line itself.

csv$.$writer Object: The project creates a csv$.$writer object, which is used to write the rows to the CSV file. This object is created by passing the file object $($opened in write mode$)$ to the csv$.$writer$()$ function.

Writing Rows: For each line analyzed, a row is written to the CSV file using the writerow$()$ method of the csv$.$writer object. This method takes a list as an argument, where each element in the list corresponds to a column in the CSV file. In this case, the list contains two elements: the sentiment and the line.

The use of the csv module in this project simplifies the process of exporting the analysis results, making it straightforward to create a structured output file that can be easily shared, viewed, and further analyzed in spreadsheet applications.

Computing the Overall Sentiment of a Document

To compute the overall sentiment of a document in the context of the sentiment you will use a simple, straightforward approach. This method involves assigning a numerical score to each sentiment category$$positive$,$ negative, neutral.