---
title: "Implicit Motives Tutorial"
description: " "
author: ""
opengraph:
  image: 
    src: "http://r-text.org/articles/text_files/figure-html/unnamed-chunk-5-1.png"
  twitter:
    card: summary_large_image
    creator: "@oscarkjell"
output: github_document #rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{implicitmotives_tutorial}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
evaluate = FALSE
```



```{r, eval = evaluate, warning=FALSE, message=FALSE, dpi=300}
#### Initial setup: Install and open the text package in an R environment (only required the first time).
#install.packages("text")
#textrpp_install()
#textrpp_initialize()

#### Load the package.
library(text)

#### 1: Load data. The following data serves as an example:  
data <- dplyr::mutate(.data = Language_based_assessment_data_8, participant_id = dplyr::row_number()) 

#### 2: Retrieve sentence- and person-level predictions. Choose between our three motives: power, achievement, or affiliation.
predictions <- textPredict(
  texts = data$satisfactiontexts,
  model_info = "implicitpower_roberta23_nilsson2024",
  participant_id = data$participant_id,
  dataset_to_merge_predictions = data)

#### 3: Examine sentence- and person-level predictions. 
predictions$sentence_predictions
predictions$person_predictions
predictions$dataset 



```

