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12 articles for “Social media analytics”
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The Role of Social Media Analytics in Integrated Marketing Communication and Understanding Consumer Behaviour: The Pathway to Optimal Customer Relationship Management
Abstract: This study explores the role of social media analytics in understanding consumer behavior within the context of Integrated Marketing Communication (IMC). Businesses now have access to a lot of data thanks to the spread of social media platforms, which can give them important insights into consumer preferences, attitudes, and behaviors. This study discusses the methodologies and tools used in social media analytics and how they can be leveraged to enhance …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 22–29 Read article
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A Comprehensive Tool for Authenticating Instagram Profiles Using Instaloader
Abstract: With the rapid growth of Instagram as a dominant social media platform, there is an increasing need for tools that allow users to extract, analyze, and monitor profile data efficiently. Instagram has become one of the leading platforms for personal branding, influencer marketing, business promotion, and public communication. As businesses and individuals seek to better understand their presence and influence on this platform, the need for reliable data extraction tools …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 93–98 Read article
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Intrinsic Evaluation of Graph Embeddings: Assessing Clustering and Community Detection Performance
Abstract: This paper presents an intrinsic evaluation of some graph embedding techniques on clustering and community detection tasks. We analyze a diverse set of embedding methods, ranging from traditional techniques such as Laplacian eigenmaps to more recent approaches like graph autoencoders, high-order proximity preserved embedding (HOPE), and graph attention network (GAT), using two widely studied datasets, Cora and CiteSeer. Our evaluation relies on two main metrics: Silhouette score with respect to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 40–48 Read article
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Social Media Analysis Using Big Data
Abstract: Social media has become an essential aspect of everyday life across different age groups, serving functions ranging from sharing personal updates to staying informed about social developments. Our objective is to harness big data to extract meaningful insights from the immense and ever-expanding volume of data generated on social media platforms. We will collect and analyze data from various social media sources, including text, images, and user interactions, using cutting-edge …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 35–46 Read article
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Enhancing User Engagement and Content Relevance: A Novel Approach to Social Media Post Recommendation System
Abstract: The social media post recommendation system is an innovative solution aimed at optimizing content delivery for users in today's digital age. Its primary motive is to tailor online experiences, ensuring users receive posts most relevant to their preferences. Various machine learning algorithms are employed to suggest related posts. This system leverages advanced algorithms and analytics, producing key results that highlight user engagement metrics and content relevance. Preliminary findings of this …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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A Mathematical Perspective on Recent Cloud-Computing Trends for Scalable and Secure Social-Media Platforms
Abstract: Cloud computing underpins modern social-media platforms by providing elastic compute, storage, and data-processing pipelines capable of absorbing highly bursty workloads. This paper surveys recent cloud-native trends—serverless and event-driven design, container orchestration, edge/CDN offload, streaming analytics, and privacy-enhancing security controls—and formalizes their impact through a compact mathematical model. We express workload volatility using arrival-rate functions, use queueing-based capacity sizing to derive auto-scaling rules, and formulate an optimization objective that balances cost …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 35–40 Read article
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Use of Modern Techniques in Library and Information Centers
Abstract: The integration of modern techniques in libraries and information centers has significantly revolutionized the way information is accessed, managed, and disseminated. Advancements in technology have moved libraries beyond their traditional roles as book repositories, enabling them to serve as dynamic information hubs. Automated Library Systems (ALS) have streamlined processes such as cataloging, circulation, and acquisitions, making it easier for patrons to search and access materials Radio Frequency Identification (RFID) technology …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 57–61 Read article
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Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
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The Impact of AI-Driven Real-Time Feedback Systems on Students’ Self-Regulated Learning and Academic Persistence in Secondary Schools, Nigeria
Abstract: Self-regulated learning (SRL) is essential for secondary school students to achieve academic success and lifelong learning competencies, particularly in contexts requiring greater learner autonomy. This expository article examines the potential of Artificial Intelligence (AI)-driven real-time feedback systems to support SRL processes—planning (forethought), monitoring (performance/control), and reflection—within Nigerian secondary education. Grounded in Zimmerman’s cyclical SRL model and Bandura’s Social Cognitive Theory, the paper conceptualises AI tools (e.g., intelligent tutoring systems, learning …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 2, 2026 Read article
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Harnessing the Power of Big Data for Personalized Marketing
Abstract: In today’s digital age, big data has revolutionized the way businesses engage with customers, driving a shift from traditional blanket marketing strategies to highly personalized campaigns. By examining large volumes of data gathered from various sources like social media, websites, and transaction records, companies can gain valuable insights into consumer behavior, preferences, and buying patterns. Personalized marketing leverages these insights into craft-tailored experiences that resonate with individual customers. For instance, …
Published in Current Trends in Information Technology · Vol. 15, Issue 1, 2025 · pp. 19–22 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article