# A Methodological Framework for AI-Driven Textual Data Analysis in Digital Media
## 4 Analyzing News Aggregation on the Israel-Lebanon Conflict:  
In order to illustrate and validate the presented methodological approach, this study conducts an analysis of data from Google News. Google News is a news aggregation platform that dynamically and continuously compiles headlines from various information sources, organizing them and serving as an amplifier of content from recognized and accredited media outlets [87]. To achieve this, a comparative analysis is performed on the news aggregated by the main pages of Google News Israel (in Hebrew) and Google News Lebanon (in Arabic). The period considered spans thirty days, covering the entire month of November 2024, a timeframe marked by escalating tensions between Israel and Hezbollah, alongside Lebanon's involvement in the broader context of conflicts in the Middle East. The relevance of this study lies in its examination of how a digital news aggregation platform reflects journalistic coverage of topics related to both countries, taking into account linguistic and editorial particularities. This case study aims to provide a descriptive perspective that aids in understanding the reported events, shedding light on the dynamics of narrative construction and its impact on information consumption in crisis scenarios. The geopolitical tensions between Israel and Lebanon have deep historical roots shaped by territorial disputes, religious divergences, and ideological conflicts [88]. Israel's occupation of southern Lebanon, Hezbollah's influence, and Iran's support for militant groups in the region have intensified these tensions over the past decades. Moreover, recent armed clashes, internal political instability in Lebanon, and the complex regional dynamics, exacerbated by foreign interference, have heightened a fragile landscape [89; 90]. In this context, the crisis between Israel and Lebanon escalated significantly in 2023 and 2024, marked by military attacks between the Israel Defense Forces and the Hezbollah paramilitary group, further aggravated by the deaths of Hezbollah leaders such as [PERSON], [PERSON], and [PERSON] [91]. Additionally, it is crucial to note that the civilian populations of both countries have been heavily impacted, whether through mass displacement or a high number of casualties [92]. This entire panorama is reflected in both local and international media and, consequently, projected onto news aggregation platforms. Google News is a news aggregation platform that indexes, organizes, and dynamically makes journalistic content available, presenting continuous variations in temporal and regional terms [87]. Aggregated news is organized through algorithmic curation that groups related content into a uniform structure, with each news item including standard elements such as the source, title, and publication date on the original source. Additionally, the platform is structured with a main page highlighting the most relevant news, complemented by specific thematic sections. An important feature is the platform's ability to offer personalization based on the user's interests and search history. However, in anonymized access scenarios, this personalization does not apply, and the content presented is generic. Google News does not provide a native API for accessing its data. Therefore, data collection was conducted through the development of a data extraction solution (web scraping) implemented using the Selenium and BeautifulSoup libraries of the Python programming language. This solution directly accesses the platform's webpage and, based on mapping the site's HTML pattern, extracts the variables of interest. It is important to note that the intrinsic features of Google News as a news aggregation platform do not include the storage of news sets delivered at specific moments, nor does it offer a pagination structure. This implies that it is not possible to retrieve retrospective information about the news presented at a given time.