Conveners
Humanities, Arts, and Social Sciences Session II
- Alex YAHJA ()
Dr
Eva Hladká
(Faculty of Informatics, Masaryk University, Brno, Czech Republic)
,
Eva Výtvarová
(Faculty of Informatics, Masaryk University, Brno, Czech Republic)
, Mr
Jan Fousek
(Faculty of Informatics, Masaryk University, Brno, Czech Republic)
3/16/16, 4:00 PM
Humanities, Arts, and Social Sciences (HASS) Applications
Oral Presentation
Computational models have large potential for enhancing our understanding of
human-environment interaction as a factor in various social and historical
phenomena [1]. One such an approach are agent-based models that provide useful
model paradigm for human behavior [3]. When coupled with geospatial data, such
models can be spatially explicit, and have variety of applications...
Dr
Frank Liu
(National Sun Yat-Sen University)
3/16/16, 4:20 PM
Humanities, Arts, and Social Sciences (HASS) Applications
Oral Presentation
In the emerging field of data science crawling social media for trends and patterns has been identified as important approach to understand the public. To social sciences, however, this approach may not be sufficient when it comes to obtain preferences and opinions about targeted subject or issues. Data collected from social media may not present expected qualitative data from which deep...
Prof.
Karl Ho
(University of Texas at Dallas)
3/16/16, 4:40 PM
Humanities, Arts, and Social Sciences (HASS) Applications
Oral Presentation
This is a proposal to present a paper at the 2016 ISGC Meeting in Academia Sinica, Taiwan ROC. This study employs new methods in analyzing large amount of poll data from all survey firms to detect so called house and mode effects in election surveys. We collect all polling results and identify house (survey firm) and mode (telephone, internet, in-person) effects on British parties' vote...
Dr
Alex Yahja
(National Center for Supercomputing Applications)
3/16/16, 5:00 PM
Humanities, Arts, and Social Sciences (HASS) Applications
Oral Presentation
With a deluge of data in this Big Data era, finding out a signal among the background of noise represents a challenge. It is almost impossible to be an expert in many subject matters needed to make rational judgments on an appealing pattern, so we rely on trust. While statistical methods help in finding correlations among data, the question is whether the data itself and/or the persons behind...
