Osamah Ghaleb | King Saud University (original) (raw)
Papers by Osamah Ghaleb
This paper aims to investigate the role of social networking for knowledge management in organiza... more This paper aims to investigate the role of social networking for knowledge management in organizations that use social networks for communication and collaboration among organizations member. Based on previous literatures this paper explains major issues relating to knowledge management and social networks and its role in successful adoption of knowledge management system. The main finding of this paper is that using social networking play role in knowledge sharing, transformation and collaboration among organization members.
Studies in Systems, Decision and Control, 2021
Twitter data generally tends to be unstructured and often very noisy, cluttered/disorganized, and... more Twitter data generally tends to be unstructured and often very noisy, cluttered/disorganized, and clothed in informal language. In this paper, we propose an intelligent Twitter data cleansing model that can solve data quality problems associated with twitter text. This model can correct a wide variety of anomalies from slangs, typos, Elongated (repeated Characters), transposition, Concatenated words, complex spelling mistakes as unorthodox use of acronyms, manifold forms of abbreviations of same words, and word boundary errors. The effects of whole range of tasks of Twitter Data Cleansing Model (TDCM) on the performance of sentiment classification utilizing feature models and three common classifiers have been investigated and evaluated. We conducted our experiments on two sets of pandemics twitter datasets: COVID-19 and Dengue datasets. The primary objective of this paper is to both increase the accuracy and the quality of twitter data and to purify and cleanse twitter data for further analysis. The experiment results seem to indicate that the accuracy of sentiment classification increases once the data quality problems associated with the Twitter text are solved. In COVID-19 twitter dataset, the best performance obtained using Random forest classifier after cleansing the data in terms of accuracy, recall, and f1-score are found to be at 84.7%, 88.5%, and 86.3% respectively. However, the best performance in terms of precision at 84.5% was observed using SVM classifier when compared to that obtained with other classifiers. Further, in the Dengue twitter dataset, the best performance for cleansing data in terms of accuracy, precision and f1-score are observed to be 81.7%, 83.7% and 88.6% respectively using Random forest classifier. The best performance in terms of recall, however, is 94.9% and was obtained using SVM classifier when compared with those obtained with other classifiers.
International Journal of Latest Trends in Engineering and Technology, 2016
The emergence advance of wireless communication and position identifying technologies offer new o... more The emergence advance of wireless communication and position identifying technologies offer new opportunities to businesses to transform the traditional electronic commerce applications into mobile computing application. Deployment of positioning-based systems technologies such as Radio Frequency Identification (RFID) and Global Positioning System (GPS)and combining this technology with mobile computing devices introduce new marketing applications such as mobile marketing and location-based services (LBS) that provide great mutual benefits for businesses and consumers, consumer are able to make transactions and receive customized tailored service based on his preferences, time, location and context in convenience way; businesses also has opportunity to widely access to large number of new customers; businesses can utilize the advance in mobile communication and computing technologies and gain customer satisfaction, thus led to improving business competitive position and increasing the revenue. Mobile computing and networking developments not only provide benefits in the area of mobile commerce applications, it also used in other applications areas such as safety/emergency, healthcare, libraries,…, etc. and provide a lot of convenience benefits to users. In the other side advanced mobile technologies LBS, mobile RFID also raise a many of privacy issues that represent a new challenges to government, businesses, and users; if these
International Journal of Intelligent Engineering and Systems, 2018
Diebold and Yimlaz, in their paper, published in 2009 and titled Measuring Financial Asset Return... more Diebold and Yimlaz, in their paper, published in 2009 and titled Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets, provided a simple and intuitive measure of interdependence between markets by measuring the returns and volatilities spillovers of 19 countries' equity markets, an approximation of global equity markets. The goal of this paper is to extend on the original paper from three perspectives. Firstly, the original paper's results shows markets interdependence results up to 2007, which does not capture the 2008 global financial crisis and its aftermath, and it is very interesting to see what happened during and after such unprecedented crisis, and to see what happened after other major and recent events such as the European sovereign debt crisis. Secondly, this study's dataset adds two key players in the global economy that are having increasing prominence: Saudi Arabia and India, increasing the number of equity markets studied to 22 countries. Thirdly, this paper uses an improved model that avoids identification schemes based on Cholesky factorization, where variance decompositions calculations depend on the ordering of the variables, by using Generalized VAR, an extension they suggested in 2009 and later used in 2012 for the same purpose of this paper but studying interdependence between different asset classes instead.
With the explosive growth of social platforms on web including blogs, products review sites, foru... more With the explosive growth of social platforms on web including blogs, products review sites, forums, Twitter and Facebook, millions of users daily share and exchange their opinions about different issues like products, events, persons or organizations on these sites. Sentiment analysis on social users’ data considered as a valuable analysis for automatically extract people opinions regarding some interested topic issues which enables to provide important information for informed decision making in different domains. With the noticed importance of sentiment analysis on social sites many applications and techniques are available. Although, performing such analysis efficiently is not travail task which can be done easily. There are a number of challenges related to sentiment analysis which needs to address and resolve. In this paper the most important challenges of sentiment analysis on social sites were highlighted and discussed with the aim to provide new directions for the intereste...
Journal of Computer Science
Indian Journal of Science and Technology, 2016
International Journal of Technology Diffusion, 2012
This research extended the Technology Acceptance Model (TAM) with perceived trust and perceived r... more This research extended the Technology Acceptance Model (TAM) with perceived trust and perceived risks (security and privacy concerns) constructs to identify the impact of these factors on Jordanian users’ intentions to adopt mobile commerce (m-commerce). An empirical test was used utilizing 132 responses from students in two public universities in Jordan. Results indicated that perceived trust, perceived usefulness, and perceived ease of use are major influencers of mobile commerce adoption. On the other hand, perceived risk factors (security and privacy concerns) were not significant in this relation. Discussion, conclusion and future work are stated at the end of this paper.
International Journal of Technology Diffusion, Apr 1, 2012
This research extended the Technology Acceptance Model (TAM) with perceived trust and perceived r... more This research extended the Technology Acceptance Model (TAM) with perceived trust and perceived risks (security and privacy concerns) constructs to identify the impact of these factors on Jordanian users' intentions to adopt mobile commerce (m-commerce). An empirical test was used utilizing 132 responses from students in two public universities in Jordan. Results indicated that perceived trust, perceived usefulness, and perceived ease of use are major influencers of mobile commerce adoption. On the other hand, perceived risk factors (security and privacy concerns) were not significant in this relation. Discussion, conclusion and future work are stated at the end of this paper.
This paper aims to investigate the role of social networking for knowledge management in organiza... more This paper aims to investigate the role of social networking for knowledge management in organizations that use social networks for communication and collaboration among organizations member. Based on previous literatures this paper explains major issues relating to knowledge management and social networks and its role in successful adoption of knowledge management system. The main finding of this paper is that using social networking play role in knowledge sharing, transformation and collaboration among organization members.
Studies in Systems, Decision and Control, 2021
Twitter data generally tends to be unstructured and often very noisy, cluttered/disorganized, and... more Twitter data generally tends to be unstructured and often very noisy, cluttered/disorganized, and clothed in informal language. In this paper, we propose an intelligent Twitter data cleansing model that can solve data quality problems associated with twitter text. This model can correct a wide variety of anomalies from slangs, typos, Elongated (repeated Characters), transposition, Concatenated words, complex spelling mistakes as unorthodox use of acronyms, manifold forms of abbreviations of same words, and word boundary errors. The effects of whole range of tasks of Twitter Data Cleansing Model (TDCM) on the performance of sentiment classification utilizing feature models and three common classifiers have been investigated and evaluated. We conducted our experiments on two sets of pandemics twitter datasets: COVID-19 and Dengue datasets. The primary objective of this paper is to both increase the accuracy and the quality of twitter data and to purify and cleanse twitter data for further analysis. The experiment results seem to indicate that the accuracy of sentiment classification increases once the data quality problems associated with the Twitter text are solved. In COVID-19 twitter dataset, the best performance obtained using Random forest classifier after cleansing the data in terms of accuracy, recall, and f1-score are found to be at 84.7%, 88.5%, and 86.3% respectively. However, the best performance in terms of precision at 84.5% was observed using SVM classifier when compared to that obtained with other classifiers. Further, in the Dengue twitter dataset, the best performance for cleansing data in terms of accuracy, precision and f1-score are observed to be 81.7%, 83.7% and 88.6% respectively using Random forest classifier. The best performance in terms of recall, however, is 94.9% and was obtained using SVM classifier when compared with those obtained with other classifiers.
International Journal of Latest Trends in Engineering and Technology, 2016
The emergence advance of wireless communication and position identifying technologies offer new o... more The emergence advance of wireless communication and position identifying technologies offer new opportunities to businesses to transform the traditional electronic commerce applications into mobile computing application. Deployment of positioning-based systems technologies such as Radio Frequency Identification (RFID) and Global Positioning System (GPS)and combining this technology with mobile computing devices introduce new marketing applications such as mobile marketing and location-based services (LBS) that provide great mutual benefits for businesses and consumers, consumer are able to make transactions and receive customized tailored service based on his preferences, time, location and context in convenience way; businesses also has opportunity to widely access to large number of new customers; businesses can utilize the advance in mobile communication and computing technologies and gain customer satisfaction, thus led to improving business competitive position and increasing the revenue. Mobile computing and networking developments not only provide benefits in the area of mobile commerce applications, it also used in other applications areas such as safety/emergency, healthcare, libraries,…, etc. and provide a lot of convenience benefits to users. In the other side advanced mobile technologies LBS, mobile RFID also raise a many of privacy issues that represent a new challenges to government, businesses, and users; if these
International Journal of Intelligent Engineering and Systems, 2018
Diebold and Yimlaz, in their paper, published in 2009 and titled Measuring Financial Asset Return... more Diebold and Yimlaz, in their paper, published in 2009 and titled Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets, provided a simple and intuitive measure of interdependence between markets by measuring the returns and volatilities spillovers of 19 countries' equity markets, an approximation of global equity markets. The goal of this paper is to extend on the original paper from three perspectives. Firstly, the original paper's results shows markets interdependence results up to 2007, which does not capture the 2008 global financial crisis and its aftermath, and it is very interesting to see what happened during and after such unprecedented crisis, and to see what happened after other major and recent events such as the European sovereign debt crisis. Secondly, this study's dataset adds two key players in the global economy that are having increasing prominence: Saudi Arabia and India, increasing the number of equity markets studied to 22 countries. Thirdly, this paper uses an improved model that avoids identification schemes based on Cholesky factorization, where variance decompositions calculations depend on the ordering of the variables, by using Generalized VAR, an extension they suggested in 2009 and later used in 2012 for the same purpose of this paper but studying interdependence between different asset classes instead.
With the explosive growth of social platforms on web including blogs, products review sites, foru... more With the explosive growth of social platforms on web including blogs, products review sites, forums, Twitter and Facebook, millions of users daily share and exchange their opinions about different issues like products, events, persons or organizations on these sites. Sentiment analysis on social users’ data considered as a valuable analysis for automatically extract people opinions regarding some interested topic issues which enables to provide important information for informed decision making in different domains. With the noticed importance of sentiment analysis on social sites many applications and techniques are available. Although, performing such analysis efficiently is not travail task which can be done easily. There are a number of challenges related to sentiment analysis which needs to address and resolve. In this paper the most important challenges of sentiment analysis on social sites were highlighted and discussed with the aim to provide new directions for the intereste...
Journal of Computer Science
Indian Journal of Science and Technology, 2016
International Journal of Technology Diffusion, 2012
This research extended the Technology Acceptance Model (TAM) with perceived trust and perceived r... more This research extended the Technology Acceptance Model (TAM) with perceived trust and perceived risks (security and privacy concerns) constructs to identify the impact of these factors on Jordanian users’ intentions to adopt mobile commerce (m-commerce). An empirical test was used utilizing 132 responses from students in two public universities in Jordan. Results indicated that perceived trust, perceived usefulness, and perceived ease of use are major influencers of mobile commerce adoption. On the other hand, perceived risk factors (security and privacy concerns) were not significant in this relation. Discussion, conclusion and future work are stated at the end of this paper.
International Journal of Technology Diffusion, Apr 1, 2012
This research extended the Technology Acceptance Model (TAM) with perceived trust and perceived r... more This research extended the Technology Acceptance Model (TAM) with perceived trust and perceived risks (security and privacy concerns) constructs to identify the impact of these factors on Jordanian users' intentions to adopt mobile commerce (m-commerce). An empirical test was used utilizing 132 responses from students in two public universities in Jordan. Results indicated that perceived trust, perceived usefulness, and perceived ease of use are major influencers of mobile commerce adoption. On the other hand, perceived risk factors (security and privacy concerns) were not significant in this relation. Discussion, conclusion and future work are stated at the end of this paper.