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Keyword: sentiment
Deep Learning Affective Computing to Elicit Sentiment Towards Information Security Policies
Information security behaviour is an integral part of modern business and has become a central theme in many research studies. One of the essential tools available that can be used to influence information security behaviour is information security policies (ISPs). These types of policies, which is mandatory in most organisations, are formalised rules and regulations…
Read More Analysis Methods and Classification Algorithms with a Novel Sentiment Classification for Arabic Text using the Lexicon-Based Approach
Social networks have become a valuable platform for tracking and analyzing Internet users’ feelings. This analysis provides crucial information for decision-making in various areas, such as politics and marketing. In addition to this challenge and our interest in the field of big data and sentiment analysis in social networks, we have dedicated this work to…
Read More Traditional and Deep Learning Approaches for Sentiment Analysis: A Survey
Presently, individuals generate tremendous volumes of information on the internet. As a result, sentiment analysis is a critical tool for automating a deep understanding of user-generated information. Of late, deep learning algorithms have shown endless promises for a variety of sentiment analysis. The purpose of sentiment analysis is to categorize different descriptions as good, bad,…
Read More Exploiting Domain-Aware Aspect Similarity for Multi-Source Cross-Domain Sentiment Classification
We propose a novel framework exploiting domain-aware aspect similarity for solving the multi- source cross-domain sentiment classification problem under the constraint of little labeled data. Existing works mainly focus on identifying the common sentiment features from all domains with weighting based on the coarse-grained domain similarity. We argue that it might not provide an accurate…
Read More Text Mining Techniques for Sentiment Analysis of Arabic Dialects: Literature Review
Social media attracts a lot of users around the world. Many reasons drive people to use social media sites such as expressing opinions and ideas, displaying their diaries and sharing them with others, social communication with family and friends and building new social relationships, learning and sharing knowledge. Written text is one of the most…
Read More Sentiment Analysis in English Texts
The growing popularity of social media sites has generated a massive amount of data that attracted researchers, decision-makers, and companies to investigate people’s opinions and thoughts in various fields. Sentiment analysis is considered an emerging topic recently. Decision-makers, companies, and service providers as well-considered sentiment analysis as a valuable tool for improvement. This research paper…
Read More Sentiment Analysis on Utilizing Online Transportation of Indonesian Customers Using Tweets in the Normal Era and the Pandemic Covid-19 Era with Support Vector Machine
Online transportation in Indonesia is a new trend of transportation that is currently used among the lower to upper society. The change in behavior began in 2011 and is growing to this day, The comments that are growing on social media are very important for the online transportation company the negative comments lower the level…
Read More Exploring the Performance Characteristics of the Naïve Bayes Classifier in the Sentiment Analysis of an Airline’s Social Media Data
Airline operators get much feedback from their customers which are vital for both operational and strategic planning. Social media has become one of the most popular platforms for obtaining such feedback. However, to analyze, categorize, and generate useful insight from the huge quantity of data on social media is not a trivial task. This study…
Read More Sentiment Analysis of Transjakarta Based on Twitter using Convolutional Neural Network
TransJakarta is one of the methods to reduce congestion in Jakarta. However, the number of TransJakarta users compared to number of private vehicle users is very small, only 24% of the total population in Jakarta. The purpose of this research is to know public opinions about TransJakarta whether positive or negative by doing sentiment analysis…
Read More Sentiment Analysis on Twitter for Predicting Stock Exchange Movement
This paper is proposed to build a model by applying two methods, namely support vector machine and nonnegative matrix factorization in the process of predicting stock market movement using twitter and historical data. The stock exchange is based on the LQ 45 stock with period from August 2018 – January 2019. The features consist of…
Read More Sentiment Analysis of Regional Head Candidate’s Electability from the National Mass Media Perspective Using the Text Mining Algorithm
Mass media plays an important role in leading public opinion, including in the election of regional head candidates. The tendency of mass media coverage can be used as a parameter to measure the strength of each regional head candidate. To analyze the tendency of media opinion, sentiment analysis is needed. In this study, text mining…
Read More Predictive Analytics in Marketing: Evaluating its Effectiveness in Driving Customer Engagement
Understanding and responding to customer feedback is critical for business success. Customer response data offers valuable insights into preferences, behaviours, and sentiment. By analysing this data, businesses can optimize strategies, enhance customer experiences, and drive growth. Many analysis have been conducted in this field, while the review covers a broad range of AI and ML…
Read More Forecasting Bitcoin Prices: An LSTM Deep-Learning Approach Using On-Chain Data
Over the past decade, Bitcoin’s unprecedented performance has underscored its po-sition as the premier asset class. Starting from an insignificant value and reaching an astounding high of around 65,000 U.S dollars in 2021 – all without a central con-trolling authority – Bitcoin’s trajectory is undoubtedly a historical feat. Its intangible nature, initially a subject of…
Read More Emotion Mining from Speech in Collaborative Learning
Affective states, a dimension of attitude, have a critical role in the learning process. In the educational setting, affective states are commonly captured by self-report tools or based on sentiment analysis on asynchronous textual chats, discussions, or students’ journals. Drawbacks of such tools include: distracting the learning process, demanding time and commitment from students to…
Read More A Survey of Big Data Techniques for Extracting Information from Social Media Data
Data mined from social media can be used in a variety of methods. The goal of this paper is to explore some of the various methods of mining data from social media and the different areas of its applications. From the analysis of other studies, it was clear that methods such as text analysis, classification,…
Read More Polarity Switch within Social Networks
It is the age of information. Social networks are the main reason why, following the increasing activity of online users. With this comes a big impact on the real world, it can be positive and highly negative as well. Therefore, research in this field is highly needed for the betterment of societal behaviors within social…
Read More Multi-Model Security and Social Media Analytics of the Digital Twin
Digital twins act through application programming interfaces to their physical counterparts to monitor, model, and control them. Beyond these traditional functions of digital twins, they must also act to secure their physical counterparts. A multi-model scheme is presented to help digital twins towards the task of securing the physical system. Additionally, this work includes an…
Read More Inferring Topics within Social Networking Big Data, Towards an Alternative for Socio-Political Measurement
This research sought to measure some socio-political indicators using millions of opinionated messages from social network sourced big data. Thus, and using an enhanced mixed method for sentiment analysis and a fusion model algorithm to infer topics from short text, this study attempted to demonstrate the value of computational approaches in measuring some phenomena in…
Read More Contextualization of the Augmented Reality Quality Model through Social Media Analytics
Augmented Reality applications are gaining popularity while maintaining novelty. Many industries are utilizing the user interface type, and use cases are becoming repeat patterns of problem solutions. Despite this rising popularity, quality has not matured nor has the technology become mainstream. Novelty must be approached as risk, and risk must be evaluated for and tested…
Read More Talk Show’s Business Intelligence on Television by Using Social Media Data in Indonesia
Knowing how and types of talk shows discussed in social media is significant to all stakeholders in a talk show’s program. There are many messages that can be found in social media that need to be noticed so the messages from the user could reach the viewer. Social media provides promising as well as challenging…
Read More Domain Independent Feature Extraction using Rule Based Approach
Sentiment analysis is one of the most popular information extraction tasks both from business and research prospective. From the standpoint of research, sentiment analysis relies on the methods developed for natural language processing and information extraction. One of the key aspects of it is the opinion word lexicon. Product’s feature from online reviews is an…
Read More Modeling Double Subjectivity for Gaining Programmable Insights: Framing the Case of Uber
The Internet is the premier platform that enable the emergence of new technologies. Online news is unstructured narrative text that embeds facts, frames, and amplification that can influence society attitudes about technology adoption. Online news sources are carriers of voluminous amounts of news for reaching significantly large audience and have no geographical or time boundaries.…
Read More Efficient Tensor Strategy for Recommendation
The era of big data has witnessed the explosion of tensor datasets, and large scale Probabilistic Tensor Factorization (PTF) analysis is important to accommodate such increasing trend of data. Sparsity, and Cold-Start are some of the inherent problems of recommender systems in the era of big data. This paper proposes a novel Sentiment-Based Probabilistic Tensor…
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