The Sound of Conflict: A Quantitative Analysis of Editorial Tone in Liberal, State-Aligned and Conservative Media Framing of the Iran-Israel Conflict (2023-2025)

This research consists of a quantitative content analysis of the editorial tone employed by three ideologically opposing newspapers, namely, Haaretz, a liberal Israeli newspaper; Kayhan, an International state-aligned Iranian newspaper; and The Wall Street Journal, a conservative American newspaper, on the Iran-Israel conflict between October 2023 and March 2025. Analyzing 677 editorials, the research is a systematic measurement of the sentiment positive, negative, and neutral across the countries of Iran, Israel, and the United States. Findings that proved statistically (using chi-square) that there is a profound and predictable ideological polarization in sentiment. Haaretz is overwhelmingly negative to Israel, 97.6% Kayhan is universally negative to Israel, 100% and the US, 94.7% while being positive to Iran, 72.4%. WSJ is strongly positive to Israel, 84.8% and is negative to Iran, 68.5%. The results demonstrate the importance and quantifiability of editorial tone as a critical instrument of the use of media as ideological expression that each media outlet uses to fulfil different geopolitical mandates of internal critique, resistance mobilization or strategic alliance reinforcement.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-27
DOI
https://doi.org/10.5281/zenodo.18803496
Primary Topic
Public Relations and Crisis Communication
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Sound of Conflict: A Quantitative Analysis of Editorial Tone in Liberal, State-Aligned and Conservative Media Framing of the Iran-Israel Conflict (2023-2025)

Abida Noureen, Mashhood Ur Rehman
Zenodo (CERN European Organization for Nuclear Research)
Public Relations and Crisis Communication
article

The Sound of Conflict: A Quantitative Analysis of Editorial Tone in Liberal, State-Aligned and Conservative Media Framing of the Iran-Israel Conflict (2023-2025)

Abida Noureen, Mashhood Ur Rehman
article en

Abstract

This research consists of a quantitative content analysis of the editorial tone employed by three ideologically opposing newspapers, namely, Haaretz, a liberal Israeli newspaper; Kayhan, an International state-aligned Iranian newspaper; and The Wall Street Journal, a conservative American newspaper, on the Iran-Israel conflict between October 2023 and March 2025. Analyzing 677 editorials, the research is a systematic measurement of the sentiment positive, negative, and neutral across the countries of Iran, Israel, and the United States. Findings that proved statistically (using chi-square) that there is a profound and predictable ideological polarization in sentiment. Haaretz is overwhelmingly negative to Israel, 97.6% Kayhan is universally negative to Israel, 100% and the US, 94.7% while being positive to Iran, 72.4%. WSJ is strongly positive to Israel, 84.8% and is negative to Iran, 68.5%. The results demonstrate the importance and quantifiability of editorial tone as a critical instrument of the use of media as ideological expression that each media outlet uses to fulfil different geopolitical mandates of internal critique, resistance mobilization or strategic alliance reinforcement.

Zenodo (CERN European Organization for Nuclear Research)
Islamia University of Bahawalpur (PK)
Peace, Justice and strong institutions
Openalex Percentile: Top 41%
Public Relations and Crisis Communication
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.