Re-Assessment Miniature print: Title: Assessment 2- Final project
Vogue: Coursework and tutorial story
Rationale: This evaluation affords a particular different for the college students to earn an pause-to-pause project in social media analytics, starting from recordsdata assortment and aiming to extract insights and pressure conclusions. The project handles social media analytics lifecycle which mimics business project’s setup.
Description: Assessment 2 is a community evaluation undertaken in pairs (groups of two college students) which checks college students’ skill to evaluate social media recordsdata using Natural Language Processing (NLP) tactics and statistical programs.
The deliveries for this evaluation:
Final project code and story for both components A and B. (65%) Disaster Title
Working out Sentiment, Issues, and Impact in Growth Discourse
Background and Motivation
Online social media platforms corresponding to Reddit assemble change into distinguished areas where professionals, practitioners, and the final public talk about complex socio-technical factors. Within the construction domain, Reddit customers often talk about topics corresponding to cost overruns, delays, law, sustainability, and the adoption of AI and digital technologies.
Nonetheless, these discussions are:
Studying Outcomes to be Assessed:
Employ masses of Application Programming Interface (API) companies and products to bag recordsdata from a amount of social media sources. Habits classic social network and statistical prognosis to render network visualisations and to admire network traits. Receive insights and perceive patterns in structured social media recordsdata using programs corresponding to correlation, regression, and classification. Extrapolate and analyse trends in unstructured-textual impart material recordsdata using pure language processing programs corresponding to sentiment prognosis and topic classification Gargantuan-scale and unstructured Emotionally charged Socially influenced, where obvious customers shape narratives bigger than others The project is to resolve what of us are speaking about, how they feel, and who influences the dialog, using computational social media analytics tactics.
Fixing this project helps organisations and researchers:
Payment public and professional sentiment Establish rising issues and considerations Detect influential voices and communities Reflect on the societal implications of digital discourse Disaster Questions Students can also mute frame their prognosis spherical the following core project questions:
What are the dominant topics mentioned in construction-connected Reddit communities? What sentiments and emotions are connected to those topics, and the intention in which attain they fluctuate across time and communities? Who are basically the most influential customers shaping these discussions, and the intention in that are communities structured? (Evolved / distinction stage) How attain LLM-based fully mostly interpretations evaluate with weak statistical and NLP-based fully mostly findings? This evaluation adopts a Knowledge Gaze Community-impressed come, in which ethical framing, to blame recordsdata employ, and reflective put collectively are handled as integral components of the analytical assignment in procedure of as put up-hoc concerns.
Dataset Knowledge Offered
Students will work with a Reddit dataset containing roughly 10,000 feedback, easy from construction-connected subreddits.
The dataset comprises (but is no longer tiny to):
physique – observation textual impart material author – Reddit username created_utc – timestamp subreddit – community name rep – upvotes/downvotes comment_id, parent_id, link_id – dialogue structure Knowledge is easy programmatically using a equipped Reddit API script, demonstrating ethical and reproducible recordsdata discover admission to.
Knowledge Considerations
Knowledge is publicly on hand Usernames should no longer be deanonymized Ethical employ and limits of social media recordsdata needs to be mentioned The Disaster Tasks (Assessment Structure) The project is split into two components, aligned with CMP7202 finding out outcomes.
Piece A: Statistical prognosis Disaster Activity A1: Knowledge Collection and Exploration
Students should:
Trail the equipped Reddit recordsdata assortment script Load and see the dataset Kind descriptive statistical prognosis (volume, assignment, scores, time trends) Disaster Activity A2: Community and Graph Prognosis
Students should:
Place a particular person interaction graph Apply centrality measures to name influential customers Detect and visualise communities Clarify what network structure finds about discourse dynamics Disaster focal level:
Impact is no longer measured by belief alone, but by quandary in the network.
Students should make stronger their statistical and network prognosis with acceptable visualizations, corresponding to temporal plots, distributions, and network graphs. All key analytical findings in Piece A needs to be visually represented and clearly defined.
Piece B – Working out Which suggests and Emotion Disaster Activity B1: Sentiment Prognosis
Students should:
Apply sentiment prognosis to Reddit feedback Analyse sentiment distribution: total by subreddit over time Discuss boundaries of computerized sentiment detection Disaster Activity B2: Topic Modelling
Students should:
Apply topic modelling (LDA, NMF, or BERTopic) Establish and worth dominant issues Analyse how topics evolve and co-exist Disaster focal level:
Issues should no longer mounted — they emerge, shift, and overlap.
Disaster Activity B3: LLM-Assisted Interpretation (Evolved) Students can also employ LLMs to:
Imprint topics Summarise clusters of debate Reflect on framing, stance, or story patterns LLM employ needs to be:
Clearly documented Significantly evaluated Primitive for prognosis, no longer story writing All analyses in Piece B needs to be accompanied by trip and interpretable visualisations, including but no longer tiny to sentiment distributions, topic frequency plots, topic evolution over time, and thematic representations. Visualisations can also mute be aged to augment interpretation and dialogue, no longer merely equipped without clarification.
Anticipated output:
Students should publish a single PDF story of a maximum of two,000 words that items the project background, methodology, results, dialogue, boundaries, and conclusion. As well to, college students should publish an executable codebase or notebook that demonstrates the guidelines assortment assignment, analytical programs applied, and the visualisations aged to augment the findings.
For advice on writing trend, referencing and tutorial abilities, please compose employ of the Centre for Tutorial Success: Centre for Tutorial Success – student make stronger | Birmingham City College (bcu.ac.uk)
Workload: 30 hours for 2000 words story and a presentation of 1000 words.
Transferable abilities: The student can assemble the good thing about doing these assessments in growing both technical and transferable abilities, which comprise:
Notify fixing Programming abilities Analytical abilities Time administration Mission administration Verbal and written communication abilities Marking Requirements
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