# Simple Sentiment Analysis

> Code from an iPython notebook, based on: http://nealcaren.web.unc.edu/an-introduction-to-text-analysis-with-python-part-1/ This notebook walks the use

**Wikidata**: [Q126087717](https://www.wikidata.org/wiki/Q126087717)  
**Source**: https://4ort.xyz/entity/simple-sentiment-analysis

## Summary
Simple Sentiment Analysis is a software tool presented as an iPython notebook designed to facilitate text analysis. It is based on an introduction to Python text analysis by Neal Caren and is utilized for network and content analysis. The tool is indexed within the Social Sciences and Humanities Open Marketplace and the Text Analysis Portal for Research.

## Key Facts
- **Entity Type:** Software
- **Format:** iPython notebook
- **Primary Use:** Network analysis, content analysis, and general analysis
- **Basis:** Derived from code located at `http://nealcaren.web.unc.edu/an-introduction-to-text-analysis-with-python-part-1/`
- **Authorship Attribution:** Associated with Neal Caren (implied by source URL)
- **Collections:** Indexed in the Social Sciences and Humanities Open Marketplace and the Text Analysis Portal for Research (TAPoR)
- **Language:** English
- **Description:** The notebook walks the user through the use of text analysis techniques.

## FAQs
### Q: What is Simple Sentiment Analysis?
A: Simple Sentiment Analysis is a software component delivered via an iPython notebook. It is designed to guide users through text analysis processes, specifically for network and content analysis.

### Q: What is the origin of the code used in Simple Sentiment Analysis?
A: The code is based on a tutorial titled "An Introduction to Text Analysis with Python Part 1" hosted by Neal Caren at the University of North Carolina at Chapel Hill.

### Q: Where can Simple Sentiment Analysis be accessed?
A: The tool is listed and described in the Social Sciences and Humanities Open Marketplace and the Text Analysis Portal for Research (TAPoR), with references dating to November 2022.

## Why It Matters
Simple Sentiment Matters serves as an accessible educational resource for researchers entering the field of computational text analysis. By utilizing the iPython notebook format, it lowers the technical barrier to entry, allowing users to execute code and view results in an interactive environment. This tool is significant for the digital humanities and social science sectors because it provides a practical, code-based approach to understanding sentiment and network analysis without requiring extensive software installation. Its inclusion in recognized research portals like TAPoR and the SSH Open Marketplace highlights its relevance as a validated tool for academic inquiry, helping scholars derive meaning from unstructured text data through Python programming.

## Notable For
- **Educational Format:** Distinctly utilizes an iPython notebook format to "walk the use" of analysis, making it a tutorial-based tool.
- **Academic Provenance:** Directly based on the educational materials of Neal Caren, a recognized figure in sociology and text analysis.
- **Specialized Utility:** While broadly a software tool, it is specifically classified for use in network analysis and content analysis.
- **Curated Recognition:** It is a vetted resource within the Text Analysis Portal for Research (TAPoR), a hub for digital humanities tools.

## Body

### Technical Overview
Simple Sentiment Analysis is classified as a non-tangible executable component of a computer, specifically identified as **software**. It functions as a tool for **network analysis**, **content analysis**, and general **analysis**. The technical implementation relies on an **iPython notebook**, an interactive computing environment that combines code, text, and visualizations.

### Origin and Development
The tool is derived from an external academic resource. The raw code and methodology are based on the web resource: *An Introduction to Text Analysis with Python Part 1* by **Neal Caren** (hosted at `nealcaren.web.unc.edu`). The provided notebook explicitly walks the user through the application of this code for analytical purposes.

### Repository and Availability
The tool is preserved and made available through two major academic channels:
*   **Social Sciences and Humanities Open Marketplace:** A European infrastructure for social sciences.
*   **Text Analysis Portal for Research (TAPoR):** A curated collection of tools for text analysis.

The entries for this tool in these databases were established or updated with references retrieved in **November 2022**. The descriptions provided in these repositories are in **English**.

## References

1. [Source](https://marketplace.sshopencloud.eu/tool-or-service/ZPNpqc)
2. [Source](https://tapor.ca/tools/590)