Convergent News? A Longitudinal Study of Similarity and Dissimilarity in the Domestic and Global Coverage of the Israeli-Palestinian Conflict

Baden, Christian; Tenenboim-Weinblatt, Keren

doi:10.1111/jcom.12272

Cited by 32 publications

(12 citation statements)

References 50 publications

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“…The importance of the specific factors driving conflict news production is further underlined by the manifold contingencies noted in how and when the above patterns arise. Despite overall co-movement, for instance, the coverage of the same conflict in the domestic and foreign media differs considerably with regard to its use of sources and their closer or more distant presentation (see also Baden and Tenenboim-Weinblatt, 2017; Tenenboim-Weinblatt et al, 2016). Synchronization between foreign and domestic media is exceptionally close in the Israeli–Palestinian conflict, which enjoys disproportionate attention not only in the global media, but also in the scholarly debate.…”

Section: Discussionmentioning

confidence: 99%

The search for common ground in conflict news research: Comparing the coverage of six current conflicts in domestic and international media over time

Baden

Tenenboim-Weinblatt

2017

Media, War & Conflict

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In its search for media influences in violent conflict, most existing scholarship has investigated the coverage of specific, salient conflict events. Media have been shown to focus on violence, sidelining concerns of reconciliation and disengaging rapidly as time proceeds. Studies have documented ethnocentric bias and self-reinforcing media hypes, which have been linked to escalation and radicalization. However, based on the existing studies, it remains hard to gauge if the unearthed patterns of media coverage are generally pervasive or limited to a few salient moments, specific conflicts or contexts. Likewise, we cannot say if different kinds of media apply similar styles of conflict coverage, or if their coverage is subject to specific contextual or outlet-specific factors. In this article, the authors compare the contents of both domestic and foreign opinion-leading media coverage across six selected conflicts over a time range of 4 to 10 years. They conduct a diachronic, comparative analysis of 3,700 semantic concepts raised in almost 900,000 news texts from 66 different news media. Based on this analysis, they trace when and to what extent each outlet focuses its attention on the conflict, highlights specific aspects (notably, violence and suffering, negotiations and peaceful solutions), and presents relevant in- and out-groups, applying different kinds of evaluation. The analysis generally corroborates the media’s tendency to cover conflict in an event-oriented, violence-focused and ethnocentric manner, both during routine periods and – exacerbated merely by degrees – during major escalation. At the same time, the analysis highlights important differences in the strength and appearance of these patterns, and points to recurrent contingencies that can be tied to the specific contextual factors and general journalistic logics shaping the coverage.

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Section: Discussionmentioning

confidence: 99%

The search for common ground in conflict news research: Comparing the coverage of six current conflicts in domestic and international media over time

Baden

Tenenboim-Weinblatt

2017

Media, War & Conflict

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“…Although there is as yet no standard method, much work has been put towards the 'unsupervised' inductive identification of frames based upon the content of the article texts 1 (e.g. Baden & Tenenboim-Weinblatt, 2017;Burscher et al, 2016;Vlieger & Leydesdorff, 2012). Nevertheless, there is a debate about the extent to which the constructs generated by these computational tools are actually frames, in the sense used by manual frame analysts, and therefore whether the new techniques are fully fit-for-purpose.…”

Section: Introductionmentioning

confidence: 99%

Computational Identification of Media Frames: Strengths, Weaknesses, and Opportunities

Nicholls

Culpepper

2020

Political Communication

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With the availability of large volumes of electronic communications data and the increasing sophistication of computational techniques, the development of automated approaches for different kinds of framing analysis is an important goal of researchers. There is as yet no standard method for the 'unsupervised' inductive identification of frames based upon the content of articles. Three groups of core approaches underlie a wide range of work in this area, and we compare three techniques based on these approaches against each other and against manual human analysts. The three techniques are a k-means clustering algorithm together with a sophisticated natural language processing (NLP)-based feature selection process; evolutionary factor analysis (EFA), a factor analysis approach; and the structural topic model (STM). We use two datasets-one very focused and one extremely broad-as examples of the kind of frame analysis problems readers may wish to attempt. Even in a highly targeted dataset, we find some distance between the frames generated by computational analysis and those manually produced by our human analysts. The details of each method have a substantial impact on frame quality and interpretation. We find that the STM approach is the most effective for our narrow-scope dataset, but that it returns definite topics, and not frames, when working on our very broad dataset. We also show that we can get results emphasizing different parts of the framing problem by combining parts of different methods as a multi-stage process, rather than viewing available methods as simple plug-and-play models.

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“…Within these factor models, the first factor captures recurring patterns in the use of concepts that are due to enduring stylistic, formal, or other properties of the journalistic writing (Motta & Baden, 2013). EFA smoothes over momentary deviations driven by the quickly shifting day-to-day coverage of events and focuses on enduring and slowly evolving patterns (Baden & Tenenboim-Weinblatt, 2017). It is therefore well-suited to revealing those subtle patterns that persistently characterize the coverage by women and men journalists.…”

Section: Methodsmentioning

confidence: 99%

Gendered Communication Styles in the News: An Algorithmic Comparative Study of Conflict Coverage

Tenenboim-Weinblatt

Baden

2018

Communication Research

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Over the past few decades, numerous studies have examined the question of whether women and men tend to use different communicative styles, strategies, and practices. In this study, we employed a high-resolution algorithmic approach to examine the role of gender in structuring conflict news discourse, focusing on a comparison between the texts produced by foreign and domestic women and men journalists in their coverage of the Israeli-Palestinian conflict and the conflict in the Democratic Republic of the Congo. Extracting recurrent semantic patterns from over 80,000 texts, we show that women and men journalists tend to interpret journalistic professionalism in slightly different ways: While women emphasize precision and professional distance, men focus more on certitude and providing orientation. Moreover, women journalists tend to give more centrality to various groups of people in their coverage. We discuss these findings in the context of scholarship on gender and language use, journalism, and conflict.

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Convergent News? A Longitudinal Study of Similarity and Dissimilarity in the Domestic and Global Coverage of the Israeli-Palestinian Conflict

Cited by 32 publications

References 50 publications

The search for common ground in conflict news research: Comparing the coverage of six current conflicts in domestic and international media over time

The search for common ground in conflict news research: Comparing the coverage of six current conflicts in domestic and international media over time

Computational Identification of Media Frames: Strengths, Weaknesses, and Opportunities

Gendered Communication Styles in the News: An Algorithmic Comparative Study of Conflict Coverage

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