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The unit IFN647 includes data pre-processing technologies for representing and analysing text, web and social media data/information. It covers the classification and clustering of text along with topic modelling methodologies for understanding the textual data. The students in the course are taught content mining, web log, and structure for better organising and retrieving data from the websites.
The students learn different methodologies of analysing social network dealing with both content and structural information compounded within the networks including review analysis, sentiment mining, etc. They understand how to deal with the ubiquitous unstructured big data and learn distinct data science and computer science complimentary approaches to conventional systems.
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The aforementioned universities or institutes in Australia are renowned for their quality of teaching and research and they offer distinct inter-related degree courses. If you are studying in any of these universities, then it is very important to follow all marking rubrics and meet deadlines while composing any assessment tasks.
This unit includes the study of following topics:
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After completing the unit successfully, students will become capable in:
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Media analytics collects information from networking sites of social media and assists the businesses to understand attitudes of users, customer sentiment, frame rich consumer profiles, and, construct efficient business strategies.
Text analytics is utilised in case of deeper insights, such as, identification of a trend or pattern from the unstructured text.
A systematic research approach to ensure no research gaps and a clear and comprehensive overview.
Get the industry-specific insights for a subject and add more value to research by adding your perspective to it.
Know how to follow the university requirements and marking rubrics. Share all assignment related issues with experts and get instant solutions.
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