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1 – 10 of 131Andreas Mölk, Manfred Auer and Mike Peters
Tourism employment is very diverse ranging from precarious, exploitative study to high-quality workplaces. However, poor employment images dominate the tourism industry, which…
Abstract
Purpose
Tourism employment is very diverse ranging from precarious, exploitative study to high-quality workplaces. However, poor employment images dominate the tourism industry, which makes attracting employees difficult. This study aims to examine the processes that lead to such image construction.
Design/methodology/approach
Using a qualitative methodology, the study develops a multilevel framing cycle comprising a media analysis of newspapers and magazines (macro-level), a conversation analysis of peer communication/negotiations (meso-level) and a content analysis of single employee/manager interviews (micro-level); and a comparative analysis of the macro-, meso- and micro-level findings.
Findings
The multilevel frame cycle identifies image-construction processes that pass through working conditions, payment, seasonality and human resource problems. These processes are shaped by the two cross-level dynamics of radicalization and attenuation. The latter consists of rationalized and repressed framings of tourism employment images (TEI) and the former consists of ideological and emotional framings.
Practical implications
Tourism stakeholders should support and participate in a pragmatic and open dialog to overcome the radicalization and attenuation of tourism employment. The key players require a new deal to end the “information warfare” on tourism employment, inaugurating a new era of collaborative and constructive employment relations.
Originality/value
This study develops a holistic and dynamic understanding of TEI by exploring how media products, peer groups and employees/managers jointly construct these images. It demonstrates how attenuation and radicalization shape poor employment images in tourism. It argues that these dynamics “lock in” the status-quo, create mutual recrimination between employers and employees and counteract common strategies that could otherwise improve employment structures and the image of tourism.
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Social networks (SNs) have recently evolved from a means of connecting people to becoming a tool for social engineering, radicalization, dissemination of propaganda and…
Abstract
Purpose
Social networks (SNs) have recently evolved from a means of connecting people to becoming a tool for social engineering, radicalization, dissemination of propaganda and recruitment of terrorists. It is no secret that the majority of the Islamic State in Iraq and Syria (ISIS) members are Arabic speakers, and even the non-Arabs adopt Arabic nicknames. However, the majority of the literature researching the subject deals with non-Arabic languages. Moreover, the features involved in identifying radical Islamic content are shallow and the search or classification terms are common in daily chatter among people of the region. The authors aim at distinguishing normal conversation, influenced by the role religion plays in daily life, from terror-related content.
Design/methodology/approach
This article presents the authors' experience and the results of collecting, analyzing and classifying Twitter data from affiliated members of ISIS, as well as sympathizers. The authors used artificial intelligence (AI) and machine learning classification algorithms to categorize the tweets, as terror-related, generic religious, and unrelated.
Findings
The authors report the classification accuracy of the K-nearest neighbor (KNN), Bernoulli Naive Bayes (BNN) and support vector machine (SVM) [one-against-all (OAA) and all-against-all (AAA)] algorithms. The authors achieved a high classification F1 score of 83\%. The work in this paper will hopefully aid more accurate classification of radical content.
Originality/value
In this paper, the authors have collected and analyzed thousands of tweets advocating and promoting ISIS. The authors have identified many common markers and keywords characteristic of ISIS rhetoric. Moreover, the authors have applied text processing and AI machine learning techniques to classify the tweets into one of three categories: terror-related, non-terror political chatter and news and unrelated data-polluting tweets.
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Kabir Md Shahin and Moyenul Hasan
This paper aims to examine the prevailing Rohingya refugee crisis from political and humanitarian perspectives and explores the political and humanitarian aspects of the Rohingya…
Abstract
Purpose
This paper aims to examine the prevailing Rohingya refugee crisis from political and humanitarian perspectives and explores the political and humanitarian aspects of the Rohingya refugee crisis.
Design/methodology/approach
Relevant literature has been reviewed for conceptual understanding. This study is descriptive and qualitative in nature and based on secondary sources of data.
Findings
The main causes of the Rohingya crisis such as political and humanitarian aspects. Issues such as discrimination and homelessness, and national security concerns that regional politics scapegoated the Rohingya to exacerbate regional tensions. Moreover, armed conflicts, political radicalization, security concerns, human rights violations and low media attention compared to other displaced families have made the future of the Rohingyas very uncertain.
Practical implications
The Rohingya crisis has far-reaching implications for domestic and regional politics as well as for relations with major world powers. In the context of regional security and geopolitics, this study provides insight into the polarization and politicization of the Rohingya minority.
Originality/value
This research offers a vital exploration of the Rohingya refugee crisis, delving into its multifaceted political and humanitarian dimensions, contributing fresh insights to address a pressing global concern.
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