## 4 Materials and Methods
### Pandora Dataset and the Baseline Approach  
The data used in our experiments stems from the social media platform Reddit ([[https://www.reddit.com/](https://www.reddit.com/)]([https://www.reddit.com/](https://www.reddit.com/)) (accessed on 28 March 2023)), and is the contribution of [PERSON] et al. [7]. As such, it represents a direct extension of their previous work that introduced the MBTI9k [84], another dataset containing MBTI labels. We decided that the PANDORA (Personality ANd Demographics Of Reddit Authors) dataset was suitable for our experiments due to the following reasons:  
1. Most of the work done in personality computing that focuses on using data for different personality models utilizes datasets coming from separate sources, with some examples being the works of [PERSON] et al. [95] and [PERSON] et al. [66]. On the other hand, in the work of some authors, while the data originates from the same source, it contains no overlap between users labelled with different personality models (e.g., the work of [PERSON] and [PERSON] [60]). To the best of our knowledge, the PANDORA dataset is the **only dataset that contains personality-relevant information for multiple personality models, with an overlap between user groups labelled with each of these models**. 2. The topical diversity of Reddit opens up the possibility of looking into the effects that interests and hobbies have on personality prediction. As a social media platform, Reddit is divided into a series of different \"subreddits\"--or smaller message boards. These message boards are often centred around a single topic or interest that individuals participating on them tend to share. **It is possible that information on these topical interests can be leveraged to improve the results of the personality prediction task**. The PANDORA dataset consists of 10,288 users that have labels for either the MBTI, Big Five or Enneagram personality models, with some users being labelled for more than one personality model. Additionally, some users also have their demographic information, such as gender or age stated. The dataset also includes 17,640,062 comments written by users in the period between the January 2015 and May 2019. Table 2 includes an overview of the dataset, providing insight into the exact number of users and comments that contain labels for either MBTI, Big Five or Enneagram personality models, as well as information on the amount of overlap between these groups. Observing the the way data are distributed, we note that none of the personality traits appear to follow a normal distribution (Figure 6). While this is not particularly unusual, it should be noted that most previous work reported a tendency towards normal distribution for the Big Five traits (e.g., the works of [PERSON] et al. [51] or work of [PERSON] and [PERSON] [96]). In the PANDORA dataset, however, most of the personality traits follow a skewed distribution, with the only exception being the _Neuroticism_ trait for which the labels seem to follow a bimodal distribution. \begin{table}
\begin{tabular}{l l l} \hline
**Personality Model** & **Number of Users** & **Number of Comments** \\ \hline Big Five & 1608 & \(3,006,566\) \\ Enneagram & 794 & \(1,458,816\) \\ MBTI & 9084 & \(15,597,237\) \\ Big Five and Enneagram & 64 & \(235,883\) \\ Big Five and MBTI & 393 & \(1,086,324\) \\ Enneagram and MBTI & 793 & \(1,457,625\) \\ All three models & 63 & \(234,692\) \\ \hline Total & \(10,288\) & \(17,640,062\) \\ \hline \end{tabular}
\end{table} 
Table 2: The number of users and comments labelled with each of the personality models in the PANDORA dataset. The data in this table were adapted from the work of [PERSON] et al. [7] CC-BY-NC. This phenomenon can be attributed to several different reasons, such as selection bias [84] or the propensity of openly stating personality traits being dictated by certain personality traits, e.g., high _Openness_.