# A Methodological Framework for AI-Driven Textual Data Analysis in Digital Media
## 4 Analyzing News Aggregation on the Israel-Lebanon Conflict:
To capture a \"snapshot\" of the news during a specific time interval, a continuous data extraction process must be carried out, even if segmented into regular intervals. Considering the analyzed temporal period (November 2024), theextraction solution was configured to perform scheduled daily accesses to the Israeli and Lebanese versions of Google News, collecting data from the main page of each version. The data obtained through the application of the web scraping solution resulted in 953 aggregated news records for the Israeli version of Google News and 990 records for the Lebanese version. The following attributes were considered in the data extraction procedures: aggregation date, source date, source name (news outlet), headline, news url, and Google News version. Figure 5 illustrates the variation in volume over the collection period, where it can be observed that the Lebanese version exhibited no quantitative fluctuations, while the Israeli version displayed variable behavior, with daily volumes ranging from 29 to 34 news items. This slight difference in volume can be attributed to various factors, such as the amount of content generated by local media outlets, the frequency of updates made by the platform, or differences in editorial policies influencing Google News' news aggregation algorithms in each region. Additionally, the geopolitical context and the intensity of newsworthy events may play a significant role, particularly in the case of the Israeli version, where coverage of conflict-related events may be more dynamic and sensitive to daily changes. The collection of news sources was carried out directly during the execution of the web scraping script, with automated identification of the field corresponding to the source in each record. The analysis of the aggregated news sources allows for mapping the diversity of sources within the platform and aids in understanding how the informational ecosystems of each region reflect local dynamics of news production and dissemination. In the case of Israel, 66 distinct sources were identified, whereas in Lebanon, the number was significantly higher, with 120 different sources. This discrepancy suggests potential structural differences in the media ecosystems of the two countries, which could be related to the number of active media outlets, the variety of sources included by Google News' algorithms in each region, as well as linguistic considerations. For instance, Hebrew is an official language exclusively in Israel, whereas Arabic is spoken across several countries. Table 1 presents the distribution of news headlines among the five leading sources for each analyzed version, highlighting characteristics related to the representativeness of the media in each context. In Israel, the most prominent sources include ynet nivtn nivtn (Ynet Yedioth Ahronoth), accounting for 19.94% of the aggregated news, followed by mako with 12.07%, and 17  
The presence of 33 LLUU 51211 (Lebanese Forces) among the leading sources in Lebanon warrants attention, as it is a news platform associated with a political party. Its prominence on Google News could suggest that political sources hold significant space within the Lebanese media ecosystem, potentially exacerbating the polarization of narratives surrounding regional conflicts. In contrast, the main Israeli sources listed in the table appear to be less associated with specific political parties, indicating a media structure more focused on commercial conglomerates and generalist portals. Aligned with the methodological procedures for data enrichment, this case study did not consider derived textual markers, meaning those directly obtained through regular expression-based procedures. On the other hand, to enhance analyses of content circulation based on Google News' news aggregation, the following contextual semantic entities were considered: the names of individuals mentioned in the news titles and the geographic location (country) referenced by the news.