M2 aims to give students insight into network and unstructured data types such as natural language and text, as well as state-of-the-art approaches to map and analyse these data. Insights and techniques gained in this module will allow students to approach real-world problems in marketing (Who are the main influencers among our customers?), management (Can we identify new discourses in the communication within our organisation?), business economics (Can language patterns be used to understand R&D intensity across companies?), political science (How is a political candidate perceived by a certain demographic, based on their social network statements?), and sociology (How is a person’s behaviour and characteristics affected by their social network?).
Upon completion, students will have built a solid knowledge foundation within network theory and analysis, computational linguistics and broader (unstructured) data processing. The module is application-focused, and thus students will gain a variety of skills to utilise relational and unstructured text data for analysis purposes.
The objective is that the student after the module possesses the necessary knowledge on:
The objective is that the student after the module possesses the necessary skills in:
The objective is that the student after the module possesses the necessary competences in:
For information see § 17.
Name of exam | M2: Network Analysis and Natural Language Processing |
Type of exam | Oral exam
Group examination with max. 6 students. |
ECTS | 5 |
Assessment | 7-point grading scale |
Type of grading | Internal examination |
Criteria of assessment | The criteria of assessment are stated in the Examination Policies and Procedures |
Danish title | M2: Network Analysis and Natural Language Processing |
Module code | KAØKO202119 |
Module type | Course |
Duration | 1 semester |
Semester | Autumn
|
ECTS | 5 |
Language of instruction | English |
Location of the lecture | Campus Aalborg |
Responsible for the module |
Study Board | Study Board of Economics |
Department | AAU Business School |
Faculty | Faculty of Social Sciences and Humanities |