Examining The Framing Of The Israel-Palestine Conflict: A Textual Analysis Of International Media News Coverage
Abstract
The purpose of this study is to investigate how the Israel-Palestine conflict is framed in news reports by worldwide media, with a particular emphasis on the October 7–November 2023 timeframe. Through an examination of articles from four well-known news websites—BBC, France24, Voice of America (VOA), and Al Jazeera—we aim to comprehend the ways in which various media platforms create stories and maybe sway public opinion. By applying the t[1]heoretical frameworks of framing theory and narrative analysis, this study analyses the visuals and language choices made by various media organizations
Through the use of a qualitative content analysis, our methodology enables a close inspection of the textual and visual components found in the news stories. This method assists us in recognizing trends, prejudices, and the general tone of the reporting. According to the data, within the designated period, Al Jazeera offered more impartial and balanced coverage of both Israel and Palestine. BBC, France24, and VOA, on the other hand, showed a propensity to present their news in a way that was more favorable to Israel and more disparaging of Palestine. The study's conclusions highlight how important media framing is in influencing how the world views the Israel-Palestine conflict. We draw attention to the differences in reporting and stress the significance of critical media literacy for viewers around the globe by contrasting the coverage from these various media channels. These findings have consequences for how media consumers should perceive news coverage, including how to recognize potential biases and underlying narratives that may color their perception of complicated geopolitical situations. By offering a nuanced viewpoint on how international events are portrayed to the public, this research adds to the larger conversation on media bias and the influence of framing in international news coverage.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
CC Attribution-NonCommercial-NoDerivatives 4.0