290093 SE Seminar in Geographic Information Science (2017S)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Fr 10.02.2017 07:00 bis Mi 22.02.2017 07:00
- Abmeldung bis Mi 15.03.2017 07:00
Details
max. 15 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
10.05.2017 13:00-16:00 – NIG, SR, 1st floor, C114
16.05.2017 08:30-11:00 – NIG, SR, 1st floor, C114
17.05.2017 13:00-16:00 – NIG, MM-Lab, 1st floor
29.05.2017 14:00-16:00 – NIG, SR, 1st floor, C114
30.05.2017 13:30-16:00 – NIG, SR, 1st floor, C114
07.06.2017 14:00-16:00 – NIG, SR, 1st floor, C114
12.06.2017 14:00-17:00 – NIG, MM-Lab, 1st floor
19.06.2017 14:00-16:00 – NIG, MM-Lab, 1st floor
20.06.2017 08:30-11:00 – NIG, SR, 1st floor, C114
21.06.2017 13:00-16:00 – NIG, SR, 1st floor, C114
26.06.2017 14:00-16:00 – NIG, MM-Lab, 1st floor
28.06.2017 13:00-16:00 – NIG, MM-Lab, 1st floor
- Dienstag 09.05. 08:30 - 11:00 Seminarraum Geographie NIG 5.OG C0528 (Vorbesprechung)
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
- Participation in class discussions (40%)
- Research design workshop (30%)
- The mini-final project (30%)
- Research design workshop (30%)
- The mini-final project (30%)
Mindestanforderungen und Beurteilungsmaßstab
Completion of all three components warrants a passing grade
1: 90–100 %
2: 80–90 %
3: 70–80 %
4: 60–70 %
5: < 60%
1: 90–100 %
2: 80–90 %
3: 70–80 %
4: 60–70 %
5: < 60%
Prüfungsstoff
No examination
Literatur
This is an incomplete and tentative selection of readings. The final list will be provided in the first class meeting. PDF files of all readings will be provided the week before the group discussion of these articles.Jurdak R, Zhao K, Liu J, AbouJaoude M, Cameron M, Newth D (2015) Understanding Human Mobility from Twitter. PLoS ONE 10(7): e0131469.
Rob Feick, Colin Robertson, A multi-scale approach to exploring urban places in geotagged photographs, Computers, Environment and Urban Systems, 2015, 53, 96-109.
Grant McKenzie, Krzysztof Janowicz, Song Gao, Li Gong. 2015. How where is when? On the regional variability and resolution of geosocial temporal signatures for points of interest. Computers, Environment and Urban Systems.
Taylor Shelton, Ate Poorthuis, Matthew Zook, Social media and the city: Rethinking urban socio-spatial inequality using user-generated geographic information, Landscape and Urban Planning 142 (2015) 198–211.
Li L, Yang L, Zhu H, Dai R (2015) Explorative Analysis of Wuhan Intra-Urban Human Mobility Using Social Media Check-In Data. PLoS ONE 10(8).
Wei, X. and X.Yao. 2014. Random Walking Value for Ranking Spatial Characteristics in Road Networks. Geographical Analysis 46(4):411-434. DOI: 10.1111/gean.12064
Ming-Hsiang Tsou , Jiue-An Yang , Daniel Lusher , Su Han , Brian Spitzberg , Jean Mark Gawron , Dipak Gupta & Li An (2013) Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): a case study in 2012 US Presidential Election, Cartography and Geographic Information Science
Signorini A, Segre AM, Polgreen PM (2011) The Use of Twitter to Track Levels of Disease Activity and Public Concern in the U.S. during the Influenza A H1N1 Pandemic. PLoS ONE 6(5): e19467. doi:10.1371/journal.pone.0019467
Jiang W, Wang Y, Tsou M-H, Fu X (2015) Using Social Media to Detect Outdoor Air Pollution and Monitor Air Quality Index (AQI): A Geo-Targeted Spatiotemporal Analysis Framework with Sina Weibo (Chinese Twitter). PLoS ONE 10(10): e0141185. doi:10.1371/journal.pone.0141185.
Arie Croitoru, Andrew Crooks, Jacek Radzikowski & Anthony Stefanidis (2013) Geosocial gauge: a system prototype for knowledge discovery from social media, International Journal of Geographical Information Science, 27:12, 2483-2508, DOI: 10.1080/13658816.2013.825724
Rob Feick, Colin Robertson, A multi-scale approach to exploring urban places in geotagged photographs, Computers, Environment and Urban Systems, 2015, 53, 96-109.
Grant McKenzie, Krzysztof Janowicz, Song Gao, Li Gong. 2015. How where is when? On the regional variability and resolution of geosocial temporal signatures for points of interest. Computers, Environment and Urban Systems.
Taylor Shelton, Ate Poorthuis, Matthew Zook, Social media and the city: Rethinking urban socio-spatial inequality using user-generated geographic information, Landscape and Urban Planning 142 (2015) 198–211.
Li L, Yang L, Zhu H, Dai R (2015) Explorative Analysis of Wuhan Intra-Urban Human Mobility Using Social Media Check-In Data. PLoS ONE 10(8).
Wei, X. and X.Yao. 2014. Random Walking Value for Ranking Spatial Characteristics in Road Networks. Geographical Analysis 46(4):411-434. DOI: 10.1111/gean.12064
Ming-Hsiang Tsou , Jiue-An Yang , Daniel Lusher , Su Han , Brian Spitzberg , Jean Mark Gawron , Dipak Gupta & Li An (2013) Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): a case study in 2012 US Presidential Election, Cartography and Geographic Information Science
Signorini A, Segre AM, Polgreen PM (2011) The Use of Twitter to Track Levels of Disease Activity and Public Concern in the U.S. during the Influenza A H1N1 Pandemic. PLoS ONE 6(5): e19467. doi:10.1371/journal.pone.0019467
Jiang W, Wang Y, Tsou M-H, Fu X (2015) Using Social Media to Detect Outdoor Air Pollution and Monitor Air Quality Index (AQI): A Geo-Targeted Spatiotemporal Analysis Framework with Sina Weibo (Chinese Twitter). PLoS ONE 10(10): e0141185. doi:10.1371/journal.pone.0141185.
Arie Croitoru, Andrew Crooks, Jacek Radzikowski & Anthony Stefanidis (2013) Geosocial gauge: a system prototype for knowledge discovery from social media, International Journal of Geographical Information Science, 27:12, 2483-2508, DOI: 10.1080/13658816.2013.825724
Zuordnung im Vorlesungsverzeichnis
(MK4-a-SE)
Letzte Änderung: Mo 07.09.2020 15:42
This seminar explores some leading-edge research topics in Geographical Information Science (GIScience) about location-based big data. Specifically, the seminar will focus on the use of location-based big data to study human activities in urban environments. Students are expected to
- critically examine current state of knowledge on the topics
- get familiar with some data derivation, analysis, and visualiation methods for location-based big data
- be motivated to develop reseasrch ideas through readings, critics, group discussions, practices, and a class projectContents:
- A quick survey of location-based big data (LBBD)
- Collecting location-based big data
- Analyzing urban mobility patterns with LBBD
- Using LBBD as public sensors
- GIS and LBBD for health researchMethod:
- For each main topic, there will be a lecture, group discussions on journal article readings, and a lab.
- Each student will develop a research idea related to any of the above topics. A class workshop will be held in early June to discuss everyone’s research idea and design. The idea can, but is not required to, be further developed into the final class project.
- Each student will complete a (mini) final project by the end of the class.