TY  - JOUR
AB  - Purpose– To evaluate and extend, existing natural language processing techniques into the domain of informal online political discussions.Design/methodology/approach– A database of postings from a US political discussion site was collected, along with self‐reported political orientation data for the users. A variety of sentiment analysis, text classification, and social network analysis methods were applied to the postings and evaluated against the users' self‐descriptions.Findings– Purely text‐based methods performed poorly, but could be improved using techniques which took into account the users' position in the online community.Research limitations/implications– The techniques we applied here are fairly simple, and more sophisticated learning algorithms may yield better results for text‐based classification.Practical implications– This work suggests that social network analysis is an important tool for performing natural language processing tasks with informal web texts.Originality/value– This research extends sentiment analysis to a new subject domain (US politics) and a new text genre (informal online discusssions).
VL  - 18
IS  - 2
SN  - 1066-2243
DO  - 10.1108/10662240810862239
UR  - https://doi.org/10.1108/10662240810862239
AU  - Malouf Robert
AU  - Mullen Tony
ED  - Yoshikiyo Kato
ED  - Sadao Kurohashi
ED  - Kentaro Inui
PY  - 2008
Y1  - 2008/01/01
TI  - Taking sides: user classification for informal online political discourse
T2  - Internet Research
PB  - Emerald Group Publishing Limited
SP  - 177
EP  - 190
Y2  - 2024/04/19
ER  -