IFN647 Assessment Answers Australia

Do you lack understanding and knowledge of the principles and technologies in context to the development of Text, Web and media analytical solutions to few of the complex and varied problems involving big data? If yes, you will not be able to write perfect IFN647 assessment answers and will require IFN647 Text Web and Media Analytics assignment help.

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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List of Institutes or Universities in Australia Offering Text Web and Media Analytics Related Degree Courses:

• Queensland University of Technology
• University of South Australia
• University of Technology Sydney
• Swinburne University of Technology
• University of New South Wales
• University of Queensland
• Deakin University
• University of New Castle

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.

Topics Related to Text Web and Media Analytics

This unit includes the study of following topics:

• Text analytics principles
• Retrieval of information
• Acquiring data from social media
• Analysis of content and sentiments
• Different text analytics methodologies
• Analysis of social media-sourced textual data for addressing a business question
• Opinion mining
• Public event detection
• Microblog and twitter mining
• Spammer detection

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Learning Outcomes of the Unit

After completing the unit successfully, students will become capable in:

• Critically analysing the present approaches to the data of social media data and data analytics
• Exploring, evaluating and analysing the uses of generalised tools of social media analytics
• Planning and undertaking a case study project which leads to the identification, assessment and framing decisions depending upon social media analytics
• Presenting research and analysis in response to the core ideas, utilises tools and skill sets in particular to data analytics

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• Check the type of assignment (projects, portfolios, essay, reports, email communications, articles, case studies, thesis or dissertation, literature review, tutorials, etc.) and formulate the solution accordingly.-*
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• Look for the required formatting style before commencing the assignment solution.
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• Incorporate their coding and intellectual skills along with conceptual knowledge, technologies of social media analytics, social media strategies, network analytics, text analytics, and alignment of analytics with business goals to solve different social media analytics assignments.
• Include all necessary elements, software, and methodologies desired in the assignment.
• After completion of the assignment solution written in a perfect layout format with proper citation of references, read the file at-least twice or thrice to rectify any error.

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