TY - JOUR
T1 - Using Twitter Data for the Study of Language Change in Low-Resource Languages
T2 - A Panel Study of Relative Pronouns in Frisian
AU - Dijkstra, Jelske
AU - Heeringa, W.J.
AU - Jongbloed-Faber, Lysbeth
AU - de Velde, H. Van
PY - 2021/4/15
Y1 - 2021/4/15
N2 - This paper investigates the usability of Twitter as a resource for the study of language change in progress in low-resource languages. It is a panel study of a vigorous change in progress, the loss of final t in four relative pronouns (dy't, dêr't, wêr't, wa't) in Frisian, a language spoken by ± 450,000 speakers in the north-west of the Netherlands. This paper deals with the issues encountered in retrieving and analyzing tweets in low-resource languages, in the analysis of low-frequency variables, and in gathering background information on Twitterers. In this panel study we were able to identify and track 159 individual Twitterers, whose Frisian (and Dutch) tweets posted in the era 2010–2019 were collected. Nevertheless, a solid analysis of the sociolinguistic factors in this language change in progress was hampered by unequal age distributions among the Twitterers, the fact that the youngest birth cohorts have given up Twitter almost completely after 2014 and that the variables have a low frequency and are unequally spread over Twitterers.
AB - This paper investigates the usability of Twitter as a resource for the study of language change in progress in low-resource languages. It is a panel study of a vigorous change in progress, the loss of final t in four relative pronouns (dy't, dêr't, wêr't, wa't) in Frisian, a language spoken by ± 450,000 speakers in the north-west of the Netherlands. This paper deals with the issues encountered in retrieving and analyzing tweets in low-resource languages, in the analysis of low-frequency variables, and in gathering background information on Twitterers. In this panel study we were able to identify and track 159 individual Twitterers, whose Frisian (and Dutch) tweets posted in the era 2010–2019 were collected. Nevertheless, a solid analysis of the sociolinguistic factors in this language change in progress was hampered by unequal age distributions among the Twitterers, the fact that the youngest birth cohorts have given up Twitter almost completely after 2014 and that the variables have a low frequency and are unequally spread over Twitterers.
U2 - 10.3389/frai.2021.644554
DO - 10.3389/frai.2021.644554
M3 - Article
SN - 2624-8212
VL - 4
JO - Frontiers in Artificial Intelligence
JF - Frontiers in Artificial Intelligence
ER -