Universität Wien FIND

Return to Vienna for the summer semester of 2022. We are planning to hold courses mainly on site to enable the personal exchange between you, your teachers and fellow students. We have labelled digital and mixed courses in u:find accordingly.

Due to COVID-19, there might be changes at short notice (e.g. individual classes in a digital format). Obtain information about the current status on u:find and check your e-mails regularly.

Please read the information on https://studieren.univie.ac.at/en/info.

136041 AR Emotion analysis in social media (2021W)

Continuous assessment of course work
MIXED

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

In addition to the sessions in class, there will be asynchronous online activities (e.g. video tutorials).

Thursday 07.10. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 14.10. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 21.10. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 28.10. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 04.11. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 11.11. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 18.11. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 25.11. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 02.12. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 09.12. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9
Thursday 16.12. 13:15 - 14:45 Hörsaal 32 Hauptgebäude, 1.Stock, Stiege 9

Information

Aims, contents and method of the course

Language inenvitable transports and encodes emotion, and this particularly holds true for language used in the social media. For example, the methodological field of sentiment analysis focuses on valence, i.e., on how positive or negative a text is perceived. In this course, students will learn how to measure emotional properties of text data (primarily using unsupervised emotion classification/inference techniques that build on lexica of emotion norms and labels). After a theoretical and methodological introduction, students will work on their own project in groups.

In this course, we will use the coding language R for doing our analyses. Strictly speaking, no preliminary knowledge in R is required (tutorials will be provided), but some experience in any programming/coding language will certainly help. Also, basic knowledge of linguistics (e.g. word categories) and mathematics (at Matura level; e.g. fractions, percentages, probabilities, linear functions,...) will be taken for granted.

Assessment and permitted materials

* Participation in class and small exercises (20 points, individual)
* Project proposal (20 points, in groups)
* Project presentation (20 points, in groups)
* Project report (40 points, in groups)

Minimum requirements and assessment criteria

* 90-100 points: sehr gut
* 80-89 points: gut
* 70-79 points: befriedigend
* 60-69 points: genügend
* 0-59 points: nicht genügend

Examination topics

Active contribution to discussions in class about conceptual and methodological aspects of emotion analysis; contribution to the groups project (literature research, data collection, coding, analysis, presentation, paper).

Reading list


Association in the course directory

S-DH (Cluster I: Language and Literature)
S-DH (Cluster III: Theatre, Film and Media)

Last modified: Th 23.09.2021 12:29