CET365 Quit-of-Direction Evaluation (Beefy marks: 100) Piece A Piece I: (42 marks) Retort all questions about this allotment. Social Media Analytics of Apple Inc. Apple Inc. is a world expertise company famend for its revolutionary hardware, tool, and providers and products, together with the iPhone, Mac, iPad, and the App Retailer. Founded in 1976, Apple has grown into one in all the sphere’s most treasured and influential brands, shaping the model forward for client electronics and digital ecosystems. Diagnosis of Apple MacBook In contemporary years, Apple has fundamentally transformed its MacBook lineup during the introduction of Apple Silicon, starting up with the M1 chip in 2020, followed by the M2 sequence. These in-condominium processors stamp Apple’s shift away from Intel chips, enabling the company to combine hardware and kit more tightly. The final consequence has been a jump in efficiency, energy efficiency, and thermal administration — with fanless designs in some units and vastly prolonged battery life changing into standout facets. This transition has reshaped the user expertise and influenced public perception of the MacBook. The M1 and M2 chips contain been widely praised by patrons and reviewers alike for offering quick, quiet, and seamless computing, even in entry-level units. As Apple continues to evolve its MacBook vary, belief how users answer to those dispositions — alongside other product facets like pricing, connectivity, and assemble — is important for informing every marketing strategy and product vogue. Sentiment % of Tweets Definite 52% Just 28% Detrimental 20% Payment 1. Sentiment Diagnosis Output (Overall Sentiment Distribution): Distribution of sentiments expressed in tweets about Apple’s MacBook computer programs. Ingredient Definite % Just % Detrimental % Key Sentiment Terms Battery Existence 65% 20% 15% “lengthy-lasting”, “energy ambiance pleasant”, “authentic”, Keyboard 35% 30% 35% “fragile”, “responsive”, “clicky”, “butterfly keys aloof if reality be told feel flimsy” Show 68% 22% 10% “elegant”, “though-provoking”, “brilliant” Ports / Dongles 10% 15% 75% “Why attain I aloof need 3 dongles to hunch in USB?” M1/M2 Chip 75% 15% 10% “sport-changer”, “ambiance pleasant”, “aloof” Customer Provider 28% 40% 32% “unhurried”, “helpful”, “no longer responsive” Efficiency 70% 18% 12% “quick”, “extremely effective”, “snug” Designate 18% 25% 57% “pricey”, “overpriced”, “no longer value it” Payment 2. Ingredient-Primarily based Sentiment Diagnosis (Sentiment by Key MacBook Facets): Sentiment breakdown by key facets of the MacBook. Entity Kind Instance Entities Frequency PRODUCT MacBook Air, MacBook Educated, M1 chip 120 ORG Apple, Amazon, Dell, HP, Microsoft, Intel, Easiest Purchase 75 GPE (Predicament) USA, Singapore, UK 60 EVENT WWDC, Shaded Friday 20 PERSON Tim Cook, tech reviewers (e.g., Marques Brownlee) 15 Payment 3. Named Entity Recognition (NER): The most frequently mentioned entities in tweets. Subject Top Key phrases Inferred Theme Summary Insight 1 battery, M1, efficiency, quick, snug, fanless Efficiency and Battery Solid user appreciation for Apple Silicon (M1/M2) chips and lengthy-lasting battery. Seen as predominant strengths. 2 value, pricey, value, pupil, top payment, value Pricing and Affordability Concerns Fashioned misfortune over high pricing; college students and value-sensitive users if reality be told feel excluded. 3 ports, dongle, usb-c, hdmi, adaptors, equipment Connectivity and Dongle Frustration Excessive frustration with the need for dongles as a result of shortcoming of usual ports like HDMI and USB-A. 4 keyboard, butterfly, keys, repair, provider, downside Keyboard and Reliability Components Ongoing dissatisfaction with keyboard durability (especially the butterfly mannequin) and repair expertise. 5 unboxing, current, assemble, graceful, launch, influencer Create Allure and Originate Pleasure Definite reactions to aesthetics, packaging, and product launch buzz, generally amplified by influencers. Payment 4. Subject Modelling Output (LDA – 5 Subjects Identified): Key subject issues mentioned in tweets, identified through LDA topic modelling. Shows 1–4 demonstrate the findings from sentiment analysis, side-based sentiment analysis, named entity recognition (NER), and topic modelling related to Apple’s MacBook computer programs. Per your overview of these results, address the following questions: Request 1 Elaborate the total sentiment distribution in Payment 1 and the side-based sentiment analysis in Payment 2, to present an explanation for customer perception of MacBooks. (6 marks) Request 2 Analyse sentiment all the arrangement in which through product facets to discover which facets Apple could perhaps aloof emphasise or enhance. (6 marks) Request 3 Entity Kind Instance Entities Frequency PRODUCT MacBook Air, MacBook Educated, M1 chip 120 ORG Apple, Intel, Easiest Purchase 75 GPE (Predicament) USA, Singapore, UK 60 EVENT WWDC, Shaded Friday 20 PERSON Tim Cook, tech reviewers (e.g., Marques Brownlee) 15 Payment 3. Named Entity Recognition (NER): The most frequently mentioned entities in tweets. See the identified named entities to assess the breadth of client conversations, together with any references to opponents or outlets. (6 marks) Request 4 Subject Top Key phrases Inferred Theme Summary Insight 1 battery, M1, efficiency, quick, snug, fanless Efficiency and Battery Solid user appreciation for Apple Silicon (M1/M2) chips and lengthy-lasting battery. Seen as predominant strengths. 2 value, pricey, value, pupil, top payment, value Pricing and Affordability Concerns Fashioned misfortune over high pricing; college students and pricesensitive users if reality be told feel excluded. 3 ports, dongle, usb-c, hdmi, adaptors, equipment Connectivity and Dongle Frustration Excessive frustration with the need for dongles as a result of shortcoming of usual ports like HDMI and USB-A. 4 keyboard, butterfly, keys, repair, provider, downside Keyboard and Reliability Components Ongoing dissatisfaction with keyboard durability (especially the butterfly mannequin) and repair expertise. 5 unboxing, current, assemble, graceful, launch, influencer Create Allure and Originate Pleasure Definite reactions to aesthetics, packaging, and product launch buzz, generally amplified by influencers. Payment 4. Subject Modelling Output (LDA – 5 Subjects Identified): Key subject issues mentioned in tweets, identified through LDA topic modelling. Evaluation the subject issues extracted from tweets to infer key subject issues of user dialogue and suggest priorities for Apple’s product vogue and marketing. (12 marks) Request 5 Formulate 4 actionable marketing or product suggestions for Apple in accordance to your interpretation of the analysis outputs. (12 marks) Piece II Subject Modelling (18 marks) Retort all questions about this allotment. This task explores the utility of social media analytics in marketing decision-making, utilizing Twitter knowledge related to Apple Inc. It is seemingly you’ll perhaps maybe be required to follow theoretical concepts and voice NLTK tools to analyse a pre-quiet dataset of tweets supplied within the csv file: Apple-Twitter-Sentiment-DFE.csv. Now not like Piece A, the guidelines on this allotment was gathered plenty of years ago, and therefore the findings could perhaps no longer be per contemporary trends. The dataset was purchased utilizing the Twitter Search API, in accordance to the search knowledge from: #AAPL OR @Apple. The tweets basically focal level on financial and stamp-related mentions of Apple, together with references to its merchandise (such because the iPhone, iPad, and iOS), stock efficiency, investor sentiment, and tech knowledge sharp the company. Request 6 Apply LDA topic modelling to title particular subject issues rising from the dataset. Analyse the outcomes by inspecting every the important thing terms that outline every cluster and the underlying tweets (the tweets that symbolize the subject issues), in account for to mark the subject issues and account for what they demonstrate about user issues or pursuits. Post your work in Python utilizing Jupyter notebook. (18 marks) Piece B Video Presentation (28 marks) Retort all questions about this allotment. Request 7 Put together a video recording of the presentation for Piece A – Piece I: Diagnosis of Apple MacBook (Questions 1 to 5) of a minimum of 5 minutes however no longer exceeding 10 minutes. Focus on with Canvas T/TG/RESIT route remark > Assignments > ECA_VIDEO for the step-by-step guide on post the video. (28 marks) Piece C – PowerPoint Presentation (12 marks) Retort all questions about this allotment. Request 8 Put together a place of PowerPoint presentation slides upon which the video presentation relies. Please demonstrate that the PowerPoint must be transformed to PDF sooner than submission to Canvas. (12 marks) —– END OF ECA PAPER —– Write My Task Stuck on CET365 knowledge analysis projects? To find customised resolution Native Singapore Writers Team 100% Plagiarism-Free Essay Top Pleasure Payment Free Revision On-Time Supply
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