Nr. | LV-Typ(en) | LV-Titel | |
5116 | PI | Online Content Analysis
Anmeldung über LPIS vom 19.02.2024 15:00 bis 25.02.2024 23:59 Abmeldung über LPIS vom 19.02.2024 15:00 bis 09.03.2024 23:59 |
LV-Leiter/in | Daniel Dan, Ph.D. |
Planpunkte Bachelor | SBWL Kurs IV - Digital Marketing SBWL Kurs IV - Marketing SBWL Kurs V - Handel und Marketing SBWL Kurs V - Marketing and Consumer Research Course IV - Digital Marketing Course V - Marketing and Consumer Research Kurs IV - Digital Marketing Kurs IV - Marketing Kurs V - Handel und Marketing Kurs V - Marketing and Consumer Research |
Semesterstunden | 2 |
Unterrichtssprache | Englisch |
Termine | ||||
Di, | 12.03.2024 | 17:00-19:00 Uhr | D4.0.019 (Lageplan) | |
Di, | 19.03.2024 | 17:00-20:00 Uhr | D4.0.019 (Lageplan) | |
Di, | 23.04.2024 | 17:00-20:00 Uhr | D4.0.127 (Lageplan) | |
Di, | 07.05.2024 | 17:00-20:00 Uhr | D4.0.127 (Lageplan) | |
Di, | 14.05.2024 | 17:00-20:00 Uhr | D4.0.127 (Lageplan) | |
Di, | 21.05.2024 | 17:00-20:00 Uhr | D4.0.136 (Lageplan) | |
Di, | 04.06.2024 | 17:00-20:00 Uhr | D4.0.127 (Lageplan) | |
Di, | 11.06.2024 | 17:00-20:00 Uhr | P | D4.0.127 (Lageplan) |
Termindownload (ical) | Termine abonnieren |
Weitere Informationen | https://learn.wu.ac.at/vvz/24s/5116 |
Kontakt: | ||
daniel.dan@wu.ac.at | ||
Inhalte der LV: | ||
The User Generated Content (UGC) on Social Media platforms produces an impressive quantity of information overload. |
||
Lernergebnisse (Learning Outcomes): | ||
|
||
Regelung zur Anwesenheit: | ||
Minimum attendance of 80%. If, due to unforeseen situations, the course is moved online, the attendance rule stays the same. The presence will be assessed by the lecturer at the beginning and at the end of each unit. Extra work must be done in order to compensate for the missing units in agreement with the lecturer. |
||
Lehr-/Lerndesign: | ||
The course is based on interactive lectures, class discussions, individual work, and group work. Classroom discussion is encouraged. Attendance and participation in class as well as interactive discussions are key ingredients to successfully learn the material of the course and will be part of your grading. Arriving late or turning in assignments over due time will affect the final grading |
||
Leistung(en) für eine Beurteilung: | ||
• In-class participation, 15%; The grading scheme is as follows: < 60% fail (5) 60% to 69,99% sufficient (4) 70% to 79,99% satisfactory (3) 80% to 89,99% good (2) >= 90% excellent (1) |
||
Teilnahmevoraussetzung(en): | ||
Some basic R language knowledge. Own laptop computer with R or RStudio installed. The enrollment in the course is done on a first-come first-served basis. The maximum number of participants is 25. |
© Wirtschaftsuniversität Wien | Kontakt