Date of Award

1-1-2017

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Languages, Literatures and Cultures

Program

Spanish

Content Description

1 online resource (iii, ix, 158 pages) : illustrations (some color), color maps.

Dissertation/Thesis Chair

Maurice Westmoreland

Committee Members

Lotfi Sayahi, Cynthia Fox

Keywords

borrowing, code switching, computer-mediated communication, contact linguistics, polylanguaging, sociolinguistics, Code switching (Linguistics), Diglossia (Linguistics), Spanish language, Social media

Subject Categories

Anthropological Linguistics and Sociolinguistics | Linguistics

Abstract

This study examines lexical borrowing, code switching, and polylanguaging in Valencian Spanish to better understand how each is used differently in oral conversation in comparison with online communication on Twitter. This study compares data collected from three published corpora of oral interviews of speakers of Valencian Spanish with data collected from Twitter profiles of individuals residing in Valencia. In each of the sources Spanish is the preferred code into which Valencian material is inserted. A unique feature of data from the published corpora is the high frequency of code switching (CS) into Valencian in instances of reported speech. With regard to frequency, Twitter users switch from Spanish into Valencian, followed by from Valencian into Spanish and then from Spanish into English. On Twitter, the most frequent type of switch found is the tag switch, which includes exhortatives, greetings and farewells, happy birthday wishes, and a variety of other types of tags and other idiomatic expressions used in a highly emblematic fashion as a way of preforming identity. Both intrasentential and intersentential switches also appear online and reflect how discourse might be organized differently online than offline. In looking at lone vs. multiword insertions, the importance of turn taking is noted and instances where speakers are not in a naturalistic conversation evidence traits which influence patterns of CS and polylanguaguing. Additionally, lexical economy is suggested as a motivating factor for CS on Twitter given the platform’s technological limitation of 140 characters per tweet.

Download

Share

COinS