Les moyens de communication médiée par ordinateur (CMO) et spécifiquement l’application WhatsApp, ont mené à des pratiques langagières innovantes au niveau de la communication écrite. Parmi ces pratiques, le recours à l’alternance codique (AC), qui est définie dans cette étude, comme un passage d’un code écrit à un autre au sein du même message. Cette étude quantitative visait à identifier automatiquement les occurrences de l’alternance codique dans les discussions de groupes WhatsApp durant 14 mois. Nous avons collecté 168 219 messages dans 30 groupes WhatsApp. L’échantillon de l’étude comprend 1 482 étudiants bilingues issus de 7 établissements universitaires libanais. Un outil informatique ‘DACA’ (détection automatique de l’alternance codique et l’arabizi) a été développé pour détecter la fréquence de ce phénomène résultant du contact des langues. Les résultats montrent que dans le corpus il y a 15 342 occurrences de l’AC soit 9,1% du total des messages. 70,5% de ces ACs sont détectés dans les messages en arabizi et 17,9% dans les messages en anglais, 10,6% dans les messages en arabe et 1% dans les messages en français. Les résultats ont montré aussi que les ACs dans les messages composés en arabizi sont assez souvent vers l’anglais (91,3% du total de ces ACs) et vers l’arabizi dans les messages composés en anglais avec le même pourcentage.
This paper is a contribution to the knowledge of WoM transmission on OSN. We specifically analyze the role of the seeding population diffusion of negative WoM. The method is based on an experiment on the Facebook fan base of an existing company. We manage to control the four elements of a successful WoM communication: the message, the social structure of the network, the characteristics of the individuals in the network, and the seeding population. We develop an original method to dissociate a seeding population from the general population and compare the diffusion of a set of negative messages distributed to both the original population and the artificially targeted subset. Results show the impact of the seeding population’s characteristics on the diffusion of consumers’ negative messages. We specifically show the impact of the carrier on the virality of the message.
Written discourse in WhatsApp discussions has been addressed in several articles in Computer-Mediated Communication (CMC). The aim of this study is to determine Lebanese universities students’ choice between Arabic and Latin keyboards while typing their online messages in WhatsApp groups and try to determine variables that affect their keyboards’ choices. We joined 33 WhatsApp discussion groups from 7 major Lebanese universities and gathered 227,059 messages written by 1,112 multilingual students. The results showed that even though Arabic keyboard is not very popular amongst some Lebanese universities’ students, it is still present in WhatsApp groups’ discussions of students especially at some faculties of the official Lebanese University where courses are taught in Arabic language. The results showed also that Arabic is widely typed in Arabizi using a Latin keyboard. This seems to be the case in the majority of universities that took part in the study. In addition, students at universities with high tuition fees and those who are having their curriculum in foreign languages use Latin keyboard more than students at some faculties of the public university.
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