---
params:
  data: data
  stopwords: stopwords
  set_title: report_title
  keep: keep
  seed: seed
title: "`r params$set_title`"  
---

```{r echo=FALSE, message=FALSE, warning=FALSE}
library(wpa)

## Get user data
data <- params$data
stopwords <- params$stopwords
keep <- params$keep
seed <- params$seed
```

Introduction
===============================================

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-------------------------------------

### Introduction

In this report, you will find analysis on **meeting subject lines**. This will allow you to refine meeting exclusion rules and identify topics that drive collaboration patterns.

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-------------------------------------

### Word cloud

```{r echo=FALSE, message=FALSE, warning=FALSE}
data %>% tm_wordcloud(stopwords = stopwords, keep = keep)
```

Word Frequency
===============================================

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-------------------------------------

### Word Frequency - Plot

```{r echo=FALSE, message=FALSE, warning=FALSE}
data %>% tm_freq(token = "words", stopwords = stopwords, keep = keep)
```

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-------------------------------------

### Word Frequency - Table

```{r echo=FALSE, message=FALSE, warning=FALSE}
data %>%
  tm_freq(
    token = "words",
    stopwords = stopwords,
    keep = keep,
    return = "table"
    ) %>%
  create_dt()
```

Phrase Frequency
===============================================

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-------------------------------------

### Phrase Frequency - Plot

```{r echo=FALSE, message=FALSE, warning=FALSE}
data %>% tm_freq(token = "ngrams", stopwords = stopwords, keep = keep)
```

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-------------------------------------

### Phrase Frequency - Table

```{r echo=FALSE, message=FALSE, warning=FALSE}
data %>%
  tm_freq(
    token = "ngrams",
    stopwords = stopwords,
    keep = keep,
    return = "table"
    ) %>%
  create_dt()
```

Word co-occurrence
===============================================

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-------------------------------------

### Word co-occurrence - Plot

```{r echo=FALSE, message=FALSE, warning=FALSE}
data %>% tm_cooc(stopwords = stopwords, seed = seed, return = "plot")
```

Column {data-width=50%}
-------------------------------------

### Word co-occurrence - Table
```{r echo=FALSE, message=FALSE, warning=FALSE}
data %>%
  tm_cooc(stopwords = stopwords, seed = seed, return = "table") %>%
  create_dt()
```

Top terms
===============================================

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-------------------------------------

### Top terms - Days

```{r echo=FALSE, message=FALSE, warning=FALSE}
data %>% subject_scan(mode = "days", stopwords = stopwords)
```

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-------------------------------------

### Top terms - Hours

```{r echo=FALSE, message=FALSE, warning=FALSE}
data %>% subject_scan(mode = "hours", stopwords = stopwords)
```