perform data analytics and visualisation on twitter data extracted using twitter API. perform text mining (topic modelling and sentiment analysis) on at least 5 articles of a recent campaign/event using News APIs.
BCU BIRMINGHAM CITY UNIVERSITY FACULTY OF COMPUTING ENGINEERING AND THE BUILT ENVIRONMENT COURSEWORK ASSIGNMENT BRIEF CMP7202 Web Social Media Analytics and Visualisation 1 Coursework Assignment Brief Postgraduate Academic Year 2021 - 2022 Module Title: Web Social Media Analytics and Visualisation Module Code: CMP7202 Assessment Title: Assessment 1 (A1): Online Quiz Assessment 2 (A2): Coursework and Academic Report Assessment Identifier: Quiz and Coursework Weighting: 100% School: Computing and Digital Technology Module Co-ordinator: Hossein Ghomeshi Hand in deadline date: • A1: Online Quiz on Week 6 • A2: Coursework and Report (two deliverables): 1. Presentation on Week10 2. Report and Code on Week 13 (Monday 9th May 2022 12:00 pm mid-day) Return of Feedback date and format 20 working days from date of submission (see Moodle for details). Re-assessment hand in deadline date: 12pm Mid-day on Monday 25th July 2022 Note: the reassessment work may be different. Support available for students required to submit a re-assessment: Timetabled revisions sessions will be arranged for the period immediately preceding the hand in date NOTE: At the first assessment attempt, the full range of marks is available. At the re-assessment attempt the mark is capped and the maximum mark that can be achieved is 50%. BIRMINGHAM CITY UNIVERSITY FACULTY OF COMPUTING ENGINEERING AND THE BUILT ENVIRONMENT COURSEWORK ASSIGNMENT BRIEF CMP7202 Web Social Media Analytics and Visualisation 2 Assessment Summary Learning outcomes of this module will be assessed with 2 various in-semester assignment tasks. A1: Online Quiz (20%) Assessment 1 is an individual interactive quiz to be conducted in week 6. The quiz will be 20 equally weighted questions consisting of multiple choice, true/false, fill in multiple gaps and short answers questions. A2: Final Project (80%) The purpose of this assessment is to give you experience Assessment 2 is an individual assessment that consists of two deliverables. Deliverable1 is a presentation on week 10 discussing findings from Part A of the final project. The presentation should also give students early formative feedback for the project progress. Deliverable 2 is the final project code and report due on week 13. 3 IMPORTANT STATEMENTS Standard Postgraduate Regulations Your studies will be governed by the BCU Academic Regulations on Assessment, Progression and Awards. Copies of regulations can be found at https://icity.bcu.ac.uk/Academic- Services/Information-for-Students/Academic-Regulations-2018-19 For courses accredited by professional bodies such as the IET (Institution of Engineering and Technology) there are some exemptions from the standard regulations, and these are detailed in your Programme Handbook Cheating and Plagiarism Both cheating and plagiarism are totally unacceptable, and the University maintains a strict policy against them. It is YOUR responsibility to be aware of this policy and to act accordingly. Please refer to the Academic Registry Guidance at https://icity.bcu.ac.uk/Academic-Registry/Information- for-Students/Assessment/Avoiding-Allegations-of-Cheating The basic principles are: • Don’t pass off anyone else’s work as your own, including work from “essay banks”. This is plagiarism and is viewed extremely seriously by the University. • Don’t submit a piece of work in whole or in part that has already been submitted for assessment elsewhere. This is called duplication and, like plagiarism, is viewed extremely seriously by the University. • Always acknowledge all of the sources that you have used in your coursework assignment or project. • If you are using the exact words of another person, always put them in quotation marks. • Check that you know whether the coursework is to be produced individually or whether you can work with others. • If you are doing group work, be sure about what you are supposed to do on your own. • Never make up or falsify data to prove your point. • Never allow others to copy your work. • Never lend disks, memory sticks or copies of your coursework to any other student in the University; this may lead you being accused of collusion. By submitting coursework, either physically or electronically, you are confirming that it is your own work (or, in the case of a group submission, that it is the result of joint work undertaken by members of the group that you represent) and that you have read and understand the University’s guidance on plagiarism and cheating. You should be aware that coursework may be submitted to an electronic detection system in order to help ascertain if any plagiarised material is present. You may check your own work prior to submission using Turnitin at the Formative Moodle Site. If you have queries about what constitutes plagiarism, please speak to your module tutor or the Centre for Academic Success. Electronic Submission of Work It is your responsibility to ensure that work submitted in electronic format can be opened on a faculty computer and to check that any electronic submissions have been successfully uploaded. If it cannot be opened it will not be marked. Any required file formats will be specified in the assignment brief and failure to comply with these submission requirements will result in work not being marked. You must retain a copy of all electronic work you have submitted and re-submit if requested. https://icity.bcu.ac.uk/Academic-Services/Information-for-Students/Academic-Regulations-2018-19 https://icity.bcu.ac.uk/Academic-Services/Information-for-Students/Academic-Regulations-2018-19 https://icity.bcu.ac.uk/Academic-Registry/Information-for-Students/Assessment/Avoiding-Allegations-of-Cheating https://icity.bcu.ac.uk/Academic-Registry/Information-for-Students/Assessment/Avoiding-Allegations-of-Cheating https://moodle.bcu.ac.uk/enrol/index.php?id=715 4 Learning Outcomes to be Assessed: 1. Utilize various Application Programming Interface (API) services to collect data from different social media sources. 2. Conduct basic social network and statistical analysis to render network visualisations and to understand network characteristics. 3. Derive insights and discover patterns in structured social media data using methods such as correlation, regression, and classification. 4. Extrapolate and analyse trends in unstructured-text data using natural language processing methods such as sentiment analysis and topic classification. Assessment Details: Title: Online Quiz Type: Online Assessment Style: Online quiz Learning Outcomes to be Assessed: • Understanding different techniques/skills in data analytics, visualisation and influence in social media. • Understanding of how to utilize various Application Programming Interface (API) services to collect data from different social media sources. • Conduct basic social network and statistical analysis to render network visualisations and to understand network characteristics. Rationale: This assessment allows students to develop a deep understanding of social network sources and characteristics, which is the core for understanding analytics and influence in social media. The assessment also helps students to develop their problem solving, analytical and time management skills. Description: The quiz will test students’ ability in the mastery of data collection, APIs, data types, ethics and Influence in social media, Role of social media analytics in predicting the future. i.e., consumer behaviour, Network Structure, Basics of Social Network Analysis – at the network level such as density, clustering classification, segmentation, degree distribution etc.; at the vertices level – centrality, betweenness, closeness; at the sub-graph level – trades communities – and network visualisation. The quiz is to be completed in 1-hour after which students will be automatically timed-out. 5 Additional information: For advice on writing style, referencing and academic skills, please make use of the Centre for Academic Success: https://icity.bcu.ac.uk/celt/centre-for-academic-success Workload: The quiz requires at least 10 hours of preparation/studying. Estimated number of words in the quiz is 1000. Transferable skills The student will benefit from doing these assessments in developing both technical and transferable skills, which include: • Problem solving • Programming skills • Analytical skills • Time management • Project management • Written communication skills Title: Assessment 2- Final project Type: Coursework and academic report Style: Practical coursework and academic report Learning Outcomes to be Assessed: • Utilize various Application Programming Interface (API) services to collect data from different social media sources. • Conduct basic social network and statistical analysis to render network visualisations and to understand network characteristics. • Derive insights and discover patterns in structured social media data using methods such as correlation, regression, and classification. • Extrapolate and analyse trends in unstructured-text data using natural language processing methods such as sentiment analysis and topic classification. Rationale: This assessment provides a unique opportunity for the student to develop an end-to-end project in social media analytics, starting from data collection and aiming to extract insights and drive conclusions. The project handles social media analytics lifecycle which mimics industry project’s setup. https://icity.bcu.ac.uk/celt/centre-for-academic-success 6 Description: Assessment 2 is an individual assessment which tests students’ ability to analyse social media data using NLP techniques and statistical methods. The deliverables for this assessment: 1. Presentation on week 10 on part A of the project. (20% presentation) 2. Final project code and report for both parts A and B on week 13. (60%) The presentation will help students to focus on how to convey analytics insights to the general audience. It will also help them in articulating their ideas and enhancing their communication and presentation skills. Presentation feedback is given by tutor and peers. Through this assessment, the student is required to: 1. Extract social media data e.g., Twitter, Facebook, YouTube. 2. Clean the collected data. 3. Apply appropriate statistical techniques for topic modelling/NLP to detect a group of words that best represent the information in the collection. 4. Process data to reveal new and interesting insights into the data, which may include recurring patterns of words in the text that may translate to the interestingness of the patterns. 5. Detect sentiments in the text that may determine the trends and topics. 6.