Mohd Ridzwan Yaakub

Mohd Ridzwan Yaakub
Universiti Kebangsaan Malaysia | ukm · Center for Artificial Intelligence Technology (CAIT)

PhD in Sentiment Analysis, QUT
Head of Sentiment Analysis Lab, UKM

About

41
Publications
24,627
Reads
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364
Citations
Citations since 2016
33 Research Items
350 Citations
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Introduction
Mohd Ridzwan Yaakub currently works at the Center for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia (UKM). Mohd Ridzwan does research in Sentiment Analysis and Online Social Networks (OSNs). Their current project is 'New Online Social Networks (OSNs) Model for Community Detection based on Minimum Spanning Tree (MST).'
Additional affiliations
November 2000 - present
National University of Malaysia
Position
  • Professor (Associate)
Description
  • Head of Sentiment Analysis Lab.
Education
January 2010 - May 2013
Queensland University of Technology
Field of study
  • Sentiment Analysis
March 2001 - November 2002
Universiti Putra Malaysia
Field of study
  • Distributed Computing
September 1997 - March 2000
Universiti Kebangsaan Malaysia
Field of study
  • Management Information System

Publications

Publications (41)
Chapter
Classification for multi-class dataset provides exciting and explorative domain to be studied in data science domain. And yet, the challenges of measuring the accuracy of multi-class performance rise an issue worth detailed research to be explored. Due to multi-class accuracy may be lower due to imbalance dataset, this paper aimed to analyze the us...
Chapter
Depression has become a public health issue. The high prevalence rate worsens all scopes of life irrespective of age and gender, affects psychological functioning, and results in loss of productivity. Early detection is crucial for expanding individuals’ lifespan and more effective mental health interventions. Social networks that expose personal s...
Article
Full-text available
A ban on palm oil imports by the European Union has become a problematic issue, especially for palm oil producers’ countries. Oil palm has been widely used in many sub-sectors, and any changes in the production side may affect many sectors that use oil palm as an input factor in their productions. This study explores the chain of the oil palm secto...
Article
Full-text available
The mobile ecosystem has experienced a dramatic change as a result of a new entrance, new application, and new business model emerged. Recent trends have shown that the mobile industry is amidst a transformation toward platformisation of the key players' business model. This situation puts a traditional business model of mobile network operators (M...
Article
Purpose –Sequel movies are very popular; however, there are limited studies on sequel movie revenue prediction. The purpose of this paper is to propose a sentiment analysis based model for sequel movie revenue prediction and to propose a missing value imputation method for the sequel revenue prediction dataset. Design/methodology/approach –A sequ...
Article
Full-text available
Corporate bankruptcy prediction is an important task in the determination of corporate solvency, that is, whether a company can meet up to its financial obligations or not. It is widely studied as it has a significant effect on employees, customers, management, stockholders, bank lending assessments, and profitability. In recent years, machine lear...
Article
Full-text available
The world is witnessing the daily emergence of a vast variety of online social networks and community detection problem is a major research area in online social network studies. The existing community detection algorithms are mostly edge-based and are evaluated using the modularity metric benchmarks. However, these algorithms have two inherent lim...
Article
Full-text available
With the growing number of literature on movie revenue prediction using machine learning techniques in recent years, a systemic review will help in strengthening the understanding of this research domain. Therefore, this article is aimed at determining the sources of data, the techniques, the features, and the evaluation metrics used in movie reven...
Article
The increase in acceptability and popularity of social media has made extracting information from the data generated on social media an emerging field of research. An important branch of this field is predicting future events using social media data. This paper is focused on predicting box-office revenue of a movie by mining people's intention to p...
Article
Full-text available
Extracting people’s opinions from social media has attracted a large number of studies over the years. This is as a result of the growing popularity of social media. People share their sentiments and opinions via these social media platforms. Therefore, extracting and analyzing these sentiments is beneficial in many ways, for example, business inte...
Article
Full-text available
Analyzing the performance of a particular approach in a field very dependent on the problem it’s aimed to solve. Artificial Neural Network (ANN) widely used for prediction in many areas including medical, environment, business intelligence and education. The uniqueness of ANN is the dynamic of hidden layer can be improvised mapped with the data pro...
Article
Full-text available
Twitter, an online micro-blogging and social networking service, provides registered users the ability to write in 140 characters anything they wish and hence providing them the opportunity to express their opinions and sentiments on events taking place. Politically sentimental tweets are top-trending tweets; whenever election is near, users tweet...
Conference Paper
Sentiment analysis in gaining more attention as it is increasingly used in multiple domains, including in interpreting educational data. The article uses sentiment analysis technique to understand the early childhood educators reported beliefs (perception) on young children's ICT use. The dataset was obtained from a comparative study of early child...
Conference Paper
Full-text available
We currently live in a data-driven society, where evolving digital technologies are dominating modern lifestyle, either for work-related activities, enhancing one’s productivity or for leisure purposes. The notion of producing more data scientists to cater for the current demand of industrial revolution 4.0 and instilling the right 21st century ski...
Article
Full-text available
Computational Thinking (CT) is not just another application of computer science principles in humans’ life. Computational Thinking has emerged as a systematic way of thinking, and problem-solving process. The awareness of inculcating CT into education, at different curricular level has started in various directions, and contexts. The article aimed...
Article
The distance between users has an effect on the formation of social network ties, but it is not the only or even the main factor. Knowing all the features that influence such ties is very important for many related domains such as location-based recommender systems and community and event detection systems for online social networks (OSNs). In rece...
Article
In sentiment analysis, the high dimensionality of the feature vector is a key problem because it can decrease the accuracy of sentiment classification and make it difficult to obtain the optimum subset of features. To solve this problem, this study proposes a new text feature selection method that uses a wrapper approach, integrated with ant colony...
Article
The rapid growth in web development has transformed today's communication. The combination of features and corresponding sentiment words (SWs) can help produce accurate, meaningful, and high-quality sentiment analysis (SA) results. There are some basic matters in the study of SA that must be understood, namely, the objects or entities that form a k...
Conference Paper
Full-text available
Computational Thinking (CT) is not just another application of computer science principles in humans’ life. Computational Thinking has emerged as a systematic way of thinking, and problem-solving process. The awareness of inculcating CT into education, at different curricular level has started in various directions, and contexts. The article aimed...
Article
Full-text available
Information on the student's cognitive abilities can help teachers to identify the strengths or potential of a student to plan a learning strategy. These data are collected through Ujian Aptitud Sekolah Rendah in year six (UASR), where the student's potential can be detected five years earlier before they take their Sijil Pelajaran Malaysia (SPM)....
Article
Full-text available
With the fast development of World Wide Web 2.0 has resulted in huge number of reviews where the consumers share their opinion about a variety of products in the websites, forum and social media such as Twitter and Instagram. For the organizations, they have to analyze customer’s behavior to find new market trends and insights. Sentiment analysis c...
Conference Paper
The paper review research conducted on young children use of digital technologies in relation with social learning domain. The paper aimed to understand young children practice of social learning via digital technology and the role of stakeholders in facilitating developmentally appropriate practice. There are three objectives of this article. Firs...
Article
Full-text available
Online social networks (OSNs) are complex time-varying networks due to the exponential growth in the number of users and the activities of those users. As the form of OSNs can change in each time frame, those working in domains such as community detection, event detection, big data analytics, recommender systems and marketing need to find a way to...
Article
Purpose Users are the key players in an online social network (OSN), so the behavior of the OSN is strongly related to their behavior. User weight refers to the influence of the users on the OSN. The purpose of this paper is to propose a method to identify the user weight based on a new metric for defining the time intervals. Design/methodology/a...
Conference Paper
Full-text available
This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performa...
Technical Report
Full-text available
Nowadays, people's opinions have become the most precious things especially in the business industry. What users think are the most difficult and complicated task handled by organizations. The way to identify the attitude of the speaker or a writer on some topics is to use sentiment analysis. Sentiment analysis has become popular and widely used in...
Article
Full-text available
Through online product reviews, consumers share their opinions, criticisms and satisfactions on the products they have purchased. However, the abundance of product reviews may be confusing and time-consuming for prospective customers as they read and analyze differing views before buying a product. The unstructured format of product reviews needs a...
Article
Full-text available
Malaysia Higher Education Institutes (HEI) have continuously designed strategies to ensure the employability of the Malaysian universities graduates, particularly in the field of Information Technology (IT). For example, Faculty of Information Science and Technology (FTSM) Universiti Kebangsaan Malaysia (UKM) has established the Industry and Profes...
Article
Full-text available
Political sentiments on social network is a trending activity whenever elections is near, users tweet about theirpreferred candidates or political parties and at times provide reasons for that. Also, political campaign is without doubt capital intensive because it amounts to huge figures when the expenditures are summed up. Therefore, to avoid such...
Conference Paper
Full-text available
Sentiment analysis functions by analyzing and extracting opinions from documents, websites, blogs, discussion forums and others to identify sentiment patterns on opinions expressed by consumers. It analyzes people's sentiment and identifies types of sentiment in comments expressed by consumers on certain matters. This paper highlights comparative s...
Article
Full-text available
Text categorization is one of key technology for organizing digital dataset. The Naiv Bayes (NB) is popular categorization method due its efficiency and less time complexity, and the Associative Classification (AC) approach has the capability to produces classifier rival to those learned by traditional categorization techniques. However, the indepe...
Article
Full-text available
Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction ab...
Conference Paper
Full-text available
As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than...
Conference Paper
Full-text available
Nowadays, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers' behavior for businesses purpose. The right decision in producing new products or services based on data about customers' characteristics means profit for organization/company. This paper proposes a new architecture for Opinio...

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Projects

Projects (3)
Project
1. To build a new reduction model suitable for pre-processing in the early cycle of the Louvain method in maximizing modularity 2. To develop new algorithm(s) that combines the network reduction model with the Louvain method so that it can speed up computational time and overcome limit resolution 3. To evaluate the performance of new algorithms with Louvain algorithm and 4 other Louvain modification algorithms in comminity detection.
Project
1. To develop new algorithm for detecting frequency of interaction path between community 2. To propose new algorithms based on MST for community detection process
Project
proposed a new algorithm that works on online social network as dynamic approach