Measuring, Understanding, and Classifying News Media Sympathy on Twitter after Crisis Events

Ali, Abdallah El; Stratmann, Tim Claudius; Park, Souneil; Schöning, Johannes; Heuten, Wilko; Böll, Susanne

doi:10.1145/3173574.3174130

Cited by 15 publications

(9 citation statements)

References 44 publications

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“…A recent study (El Ali et al 2018) examined the connection between cultural factors and sympathy bias in the OSN coverage of global terror attacks. In particular, El Ali et al examined tweets authored by Western news media outlets and Arab news media outlets about two terror attacks -the 2015 Beirut attack and the 2015 Paris attack.…”

Section: Use Of Social Media In Crisis Communicationmentioning

confidence: 99%

An analysis of emotion-exchange motifs in multiplex networks during emergency events

Kušen

Strembeck

2019

Appl Netw Sci

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In this paper, we present an analysis of the emotion-exchange patterns that arise from Twitter messages sent during emergency events. To this end, we performed a systematic structural analysis of the multiplex communication network that we derived from a data-set including more than 1.9 million tweets that have been sent during five recent shootings and terror events. In order to study the local communication structures that emerge as Twitter users directly exchange emotional messages, we propose the concept of emotion-exchange motifs. Our findings suggest that emotion-exchange motifs which contain reciprocal edges (indicating online conversations) only emerge when users exchange messages that convey anger or fear, either in isolation or in any combination with another emotion. In contrast, the expression of sadness, disgust, surprise, as well as any positive emotion are rather characteristic for emotion-exchange motifs representing one-way communication patterns (instead of online conversations). Among other things, we also found that a higher structural similarity exists between pairs of network layers consisting of one high-arousal emotion and one low-arousal emotion, rather than pairs of network layers belonging to the same arousal dimension.

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Section: Use Of Social Media In Crisis Communicationmentioning

confidence: 99%

An analysis of emotion-exchange motifs in multiplex networks during emergency events

Kušen

Strembeck

2019

Appl Netw Sci

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“…In a study by Ali et al (2018), the authors investigate bias in Twitter coverage between western and Arab media after the Beirut and Paris terror attacks of 2015. The paper studies sympathy and sentiment labels for 2,390 tweets across four languages (English, Arabic, French, and German).…”

Section: Terror News Coverage: the Digital Turnmentioning

confidence: 99%

News Discourse of Terror Attacks on Twitter: Comparative Analysis of CNN and Al Jazeera’s Coverage of 2015 Islamic State Attacks in Beirut and Paris

Kumar¹,

Jaggi²

2020

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The period between 2014 and 2016 saw the rise of the radical Islamist terrorist group Islamic State (IS), which committed acts of terrorism in not only Syria and Iraq but also unleashed violence in the rest of the world. Twitter took the lead in being the source of receiving and giving quick updates on terror news. However, a key question that arises is about balanced coverage. Media made enormous efforts to humanize the terror attacks in the West, while what was happening in West Asia (Middle East) was constructed from a partisan political position. The researchers studied the coverage of the Beirut attack and the Paris attack, both of which took place in November 2015. The Twitter handles of Al Jazeera and CNN's Breaking News were used to conduct the study. The data analysis establishes that there was a clear imbalance while covering Islamic State attacks in Paris and Beirut, respectively. The Paris attack received far more coverage from both CNN and Al Jazeera in terms of quantum and nature of issues a ddr essed.

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“…In the context of cross-lingual analytics, events play a particularly important role: When an event breaks out, this event is usually reported by a large number of sources, whose coverage highly varies across language communities [3]. This phenomenon becomes visible when using EventRegistry, a tool that allows crosslingual exploration of news articles which are assigned to event clusters [15].…”

Section: Related Workmentioning

confidence: 99%

EventKG+Click: A Dataset of Language-specific Event-centric User Interaction Traces

Abdollahi,

Gottschalk,

Demidova

2020

Preprint

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An increasing need to analyse event-centric cross-lingual information calls for innovative user interaction models that assist users in crossing the language barrier. However, datasets that reflect user interaction traces in cross-lingual settings required to train and evaluate the user interaction models are mostly missing. In this paper, we present the EventKG+Click dataset that aims to facilitate the creation and evaluation of such interaction models. EventKG+Click builds upon the eventcentric EventKG knowledge graph and language-specific information on user interactions with events, entities, and their relations derived from the Wikipedia clickstream.

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Measuring, Understanding, and Classifying News Media Sympathy on Twitter after Crisis Events

Cited by 15 publications

References 44 publications

An analysis of emotion-exchange motifs in multiplex networks during emergency events

An analysis of emotion-exchange motifs in multiplex networks during emergency events

News Discourse of Terror Attacks on Twitter: Comparative Analysis of CNN and Al Jazeera’s Coverage of 2015 Islamic State Attacks in Beirut and Paris

EventKG+Click: A Dataset of Language-specific Event-centric User Interaction Traces

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