Nowcasting user behaviour with social media and smart devices on a longitudinal basis :
نام عام مواد
[Thesis]
نام نخستين پديدآور
Tsakalidis, Adam
عنوان اصلي به قلم نويسنده ديگر
from macro- to micro-level modelling
وضعیت نشر و پخش و غیره
نام ناشر، پخش کننده و غيره
University of Warwick
تاریخ نشرو بخش و غیره
2018
یادداشتهای مربوط به پایان نامه ها
جزئيات پايان نامه و نوع درجه آن
Ph.D.
کسي که مدرک را اعطا کرده
University of Warwick
امتياز متن
2018
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
The adoption of social media and smart devices by millions of users worldwide over the last decade has resulted in an unprecedented opportunity for NLP and social sciences. Users publish their thoughts and opinions on everyday issues through social media platforms, while they record their digital traces through their smart devices. Mining these rich resources offers new opportunities in sensing real-world events and indices (e.g., political preference, mental health indices) in a longitudinal fashion, either at the macro (population)-, or at the micro(user)-level. The current project aims at developing approaches to "nowcast" (predict the current state of) such indices at both levels of granularity. First, we build natural language resources for the static tasks of sentiment analysis, emotion disclosure and sarcasm detection over user-generated content. These are important for opinion monitoring on a large scale. Second, we propose a general approach that leverages textual data derived from generic social media streams to nowcast political indices at the macro-level. Third, we leverage temporally sensitive and asynchronous information to nowcast the political stance of social media users, at the micro-level using multiple kernel learning. We then focus further on the micro-level modelling, to account for heterogeneous data sources, such as information derived from users' smart phones, SMS and social media messages, to nowcast time-varying mental health indices of a small cohort of users on a longitudinal basis. Finally, we present the challenges faced when applying such micro-level approaches in a real-world setting and propose directions for future research.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
H Social Sciences (General)
موضوع مستند نشده
Q Science (General)
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )