cm013.Rmd

---
title: "Text analysis: fundamentals and sentiment analysis"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(cache=TRUE)
```

# cm013 - November 7, 2016

## Overview

* Identify the basic workflow for conducting text analysis
* Define *sentiment analysis* and review how sentiment analysis was used in *Conservatives report, but liberals display, greater happiness*
* Define the *tidy text format*
* Demonstrate how to conduct sentiment analysis using David Robinson's [Text analysis of Trump's tweets confirms he writes only the (angrier) Android half](http://varianceexplained.org/r/trump-tweets/)

## Slides and links

* [Notes from class](text01.html)
* [Slides](extras/cm013_slides.html)

## To do for Wednesday

* [Finish homework 6](hw06-webdata.html)
* Review chapters 1-4 in [*Tidy Text Mining with R*](http://tidytextmining.com/) if you have not already
* Chapters 5-7 in [*Tidy Text Mining with R*](http://tidytextmining.com/)
* [Blei, D. M. (2012). Probabilistic topic models. *Communications of the ACM*, 55(4), 77-84.](http://cacm.acm.org/magazines/2012/4/147361-probabilistic-topic-models/fulltext)