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A Sociolinguistic Study of Code Choice among Saudis on Twitter

dc.contributor.authorAl Alaslaa, Saeed
dc.date.accessioned2018-06-07T17:47:13Z
dc.date.availableNO_RESTRICTION
dc.date.available2018-06-07T17:47:13Z
dc.date.issued2018
dc.date.submitted2018
dc.identifier.urihttps://hdl.handle.net/2027.42/144071
dc.description.abstractThe present study is an attempt to explore a new dimension of language use: how Arabic is utilized in the social media, Twitter in particular. It attempts to examine codeswitching (CS) in its written form between standard Arabic (SA) and Saudi dialect (SD). It aims to answer three research questions, namely: 1. What are the functions of using CS on Saudi Twitter? Are these functions different from the functions of CS in face-to-face interactions? 2. Do patterns of CS differ by gender and education? 3. Do patterns of CS differ by topic? The current study adopts the sociolinguistic approach and provides a qualitative descriptive and quantitative analysis of 7350 tweets which were collected between December 2016 and July 2017, from 210 Saudi Twitter accounts diversified in terms of gender and education. The goal was to compare the motivations for CS in the written form with those motivations that have been identified in face-to-face interactions and to explore whether CS patterns would differ by gender and education. An additional 500 tweets were collected to investigate whether or not CS patterns would change by topic. The findings revealed that the Saudi Twitter community utilized SA more than the SD. The study revealed that CS to SA is correlated with prestige, importance, sophistication, and seriousness. It revealed that the Saudi Twitter community switched to SA for the following social motivations: 1. to introduce formulaic expressions 2. to emphasize a point 3. to quote 4. to shift from comic to serious tone 5. to take a pedantic stand. In contrast, the SD or the Low variety is associated with sarcasm, informality, low-prestige, and everyday topics. It revealed that the Saudi Twitter community switched to the SD for the following social motivations: 1. for a specific intended meaning 2. for sarcasm and criticism 3. for quotations 4. for exemplifying and simplification 5. for introducing daily-life sayings 6. for scolding and personal attack or insult 7. for common usage. Regarding the role of topic in CS patterns, the present study provided evidence against Ferguson’s prediction (1959) in which he associated code choice with the topic and situation. It revealed that CS occurred in different contexts that varied in their formality and informality. Therefore, the study provided evidence that CS occurs to perform intended functions. As for gender, the study found that men utilized SA more than women, and this confirms previous findings of Ibrahim (1986), and Abd-El-Jawad (1987), Badawi (1973), and Haeri (1996a), Schmidt (1974), and Walters (1996) that women with the same level of education as men use SA less than men. Regarding education, the present study found that the Saudi Twitter users with high and college education used SA more than their counterparts with less than college education. However, the current study should have considered age in addition to gender and education, because education by itself might be “a proxy variable” that could act on behalf of other less obvious independent variables (Al-Wer 2009). The findings of the present study suggest studying each community independently as each community differs in terms of its social variables, language attitudes, perceptions, and language policies. Finally, the study emphasizes the importance of teaching SA to Arabic learners, placing less focus on dialects to learners due to the stability of SA, and designing as well as developing curriculums accordingly.
dc.language.isoen_US
dc.subjectcodeswitching
dc.subjectArabic linguistics
dc.subjectArabic sociolinguistics
dc.subjectsocial media
dc.subjectTwitter
dc.subjectbidialectal codeswitching
dc.titleA Sociolinguistic Study of Code Choice among Saudis on Twitter
dc.typeThesisen_US
dc.description.thesisdegreenamePhDen_US
dc.description.thesisdegreedisciplineNear Eastern Studies
dc.description.thesisdegreegrantorUniversity of Michigan, Horace H. Rackham School of Graduate Studies
dc.contributor.committeememberAlhawary, Mohammad
dc.contributor.committeememberBaptista, Marlyse
dc.contributor.committeememberAlbirini, Abdulkafi
dc.contributor.committeememberRammuny, Raji M
dc.subject.hlbsecondlevelMiddle Eastern, Near Eastern and North African Studies
dc.subject.hlbtoplevelSocial Sciences
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/144071/1/saeedaa_1.pdf
dc.identifier.orcid0000-0002-0527-2334
dc.identifier.name-orcidAl Alaslaa, Saeed; 0000-0002-0527-2334en_US
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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