## 4 Dataset
### Dataset Description and Preparation
The second group consisted of all cities with a population of between 10,000 and 70,000, such as Velika Gorica, Pula, Slavonski Brod, Karlovac, Varazdin, and others. The third group included all the Croatian cities with fewer than 10,000 inhabitants. The NUTS classification [53] is a statistical standard used to divide a country's territory (in this case, the Republic of Croatia) into spatial units for regional statistical analysis. The application of the NUTS classification began when Croatia joined the European Union, dividing its territory into three levels. The lowest level (HR NUTS 3) consists of administrative units, which are 21 counties in the case of Croatia. The next level (HR NUTS 2) comprises four non-administrative (regional) units depicted in Figure 1, created by county grouping. The highest level (HR NUTS 1) encompasses the entire territory of the Republic of Croatia as a single administrative unit. For our dataset, we chose the second-level division (NUTS 2) for further analysis, as it provided additional information about the contestants without overburdening the models with too many possibilities, as would be the case with the county-level division. Additionally, although not all the counties were represented by contestants in the quiz, all four non-administrative regions were. Table 6 shows the region codes used according to the NUTS 2 classification. Most of the contestants were asked by the host about their plans for spending the prize money in case they managed to win on the show. Despite the wide variety of answers, we defined four categories of the intended use of the prize money, as presented in Table 7. The first category included intentions that we identified as basic life expenses, such as car purchases, money savings, or real estate investments. The second category, titled \"Extravagant purposes\" included all the unusual ideas for spending money, such as \"buying shoes\", \"participating just for fame\", \"presidential election campaign\", \"giving money to a spouse\", or simply stating \"it does not matter\". The third category consisted of travel, wellness activities, treating friends, or other common hobbies, such as sports or music. The final category included noble uses of the prize money, such as funding one's education (e.g., a PhD degree or driving lessons), publishing a novel, or donating money to a charity. Some contestants mentioned multiple intended uses for the prize money. In such cases, the first-mentioned purpose was selected. The final feature describing the contestants was whether the chasers recognized them from previous TV shows or pub quizzes. When the host announced the contestant's name, the camera usually focused on the team of chasers, revealing their reaction to the upcoming contestant. In cases where they were familiar with the contestant, they usually made a brief comment about their past performance in other quizzes or their reputation on the quiz scene. Whether the chasers were already familiar with the contestant was encoded with a value of 1 if true and 0 otherwise. In addition to the contestant-related data, the offers also had to be converted to purely numerical values. The prize money and time were already expressed as numbers, but it was also important to consider the order in which the chasers appeared in the offers. To preserve the chaser's anonymity, their names were replaced with the assigned identifier numbers (from Chaser #1 to Chaser #5), which remained consistent across all the instances. A column was added for each chaser to indicate the offer in which they appeared. For example, if Chaser #2 and Chaser #3 appeared in the first offer, Chaser #5 joined them in the second, Chaser #4 in the third, and Chaser #1 in the fourth, the record for that contestant would look as presented in Table 8. As mentioned in the Introduction (Section 1), we also analyzed two scenarios where we only considered the information about which chasers participated in the second phase of the game, regardless of their order of appearance.