## 4 Experimental Set-Up
### Datasets
#### 4.1.2 Colombian Conflict Dataset  
The third dataset used in this work comes from the Universidad Catolica de Pereira. It comprises a collection of journalistic articles written by young university students in Colombia, which is a product of the project: Analytical Center of University Cultural Productions in the Context of the Conflict (caPAZ), funded by the Ministry of Science, Technology, and Innovation (Minciencias) and the National Center for Historical Memory (CNM) of Colombia (under the code: 1349-872-76354, agreement 872 of 2020). This corpus includes news written by the 24 college media of the Colombian Network of College Journalism from 2001 to 2021. The dataset includes digital, printed, sound, and audiovisual news, for 3049 news items and 3,451,486 words related to the armed conflict, the memory of the victims, and the peace process in Colombia. For the case of this article, we will focus on the news articles that appeared on the web pages of the 24 college media because they gave us greater diversity, greater reliability in the extraction process, and a more significant impact due to their high production. However, we only used the news articles from 8 college media since they were the ones with more than 50 news items. In conclusion, a total of 2373 digital news articles were analyzed, see Table 2. These news items were collected through a web-scraping technique, using three lemmatized keywords (conflicto armado, memoria de las victimas, and proceso de paz), with the aim of identifying these regular expressions in the logical operators that run through the HTML structure of each Web page. Likewise, a web-crawling technique was used to explore the addressing links of each page and build a relevant relationship graph. The 2373 news items were converted into raw text format.txt. Finally, the documents' semantic orientations are generated by performing a lexicometry analysis using the Alceste-Reinert method for textual data clustering [47]. Such dataset is publicly available ([[https://zenodo.org/record/6384840#.Yj5](https://zenodo.org/record/6384840#.Yj5) Av-fMJJPZ]([https://zenodo.org/record/6384840#.Yj5](https://zenodo.org/record/6384840#.Yj5) Av-fMJJPZ), accessed on 31 March 2021).  
The Alceste-Reinert method focuses on the identification of lexical worlds. This method makes it possible, through statistical analysis, to identify the appearance of specific forms in the content of a speech. [PERSON]'s main thesis [48] asserts that all discourse expresses a system of lexical words, which organize thought and give coherence to what is described by the enunciators. These lexical worlds are identified through top-down hierarchical clustering exercises and expressed in textual dendrograms, namely, a tree-shaped diagram to represent the hierarchy of categories according to the degree of similarity and shared characteristics. For the case of this research, textual dendrograms were generated for each medium analyzed. These eight dendrograms compile the 2373 news items. The labeling process consisted of qualitative analysis through direct observation of each textual dendrogram. Polarity coding was performed by an investigator, who labeled the material as positive and negative. The assignment of the said label was made with each percentage community expressed in the dendrograms. It is essential to clarify that the labeling process was done for each analyzed college media and not for each news item in the corpus.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Media** & **N\({}^{\circ}\) News** \\ \hline Universidad de Ibague & 89 \\ Universidad del Valle & 60 \\ Universidad de la Sabana & 281 \\ Uniminuto & 508 \\ Jorge Tadeo Lozano & 800 \\ Santiago de Cali & 94 \\ Universidad del Rosario & 175 \\ Universidad Autónoma de Bucaramanga & 366 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Number of news per media in the Colombian conflict corpus.