Vimala Balakrishnan

Bio: Vimala Balakrishnan is an academic researcher from University of Malaya. The author has contributed to research in topics: Social media & Sentiment analysis. The author has an hindex of 19, co-authored 120 publications receiving 1578 citations. Previous affiliations of Vimala Balakrishnan include Multimedia University & Information Technology University.

Students' learning styles and their effects on the use of social media technology for learning

Abstract: The participatory, collaborative, and independent learning styles were investigated.The social media acceptance model was proposed.The factors Self and Performance were found to influence students' intention of using social media.The factor Self had the greatest influence on all learning styles.Students with participatory style focused more on Self than those of the collaborative style did. Students with different learning styles approach learning differently. With the rise of social media technologies, investigating the effect of these styles on their intentions to use social media for learning has become all the more important. This study explored the factors affecting students' intentions to use social media for learning based on their learning styles (i.e., participatory, collaborative, and independent), using the social media acceptance model. By convenience sampling, 300 Malaysian students were recruited via an online survey (Nparticipatory=116; Nindependent=97; and Ncollaborative=87). The survey was prepared by drawing on the social media acceptance model. It was piloted before the final data collection step was conducted in August 2013. The demographic details of the students were analyzed using Statistical Program for Social Sciences 21, while path modeling and multivariate analyses were conducted using SmartPLS 2.0. The results revealed the significant effect of Self and Performance on students' intentions to use social media regardless of their learning styles. A pair-wise comparison revealed that Self was more significant in participatory students than in collaborative students. Effort was found to be the least significant factor, indicating the popularity of social media among students. Further insight into the different factors that drive students with different learning styles to use social media will help educators use this technology to assist learning more effectively.

Cyberbullying among young adults in Malaysia

Abstract: The study explored cyberbullying prevalence among young adults in Malaysia.Social media emerged as the primary tool used.No significant differences for gender and age on cyberbullying activities.Internet frequency significantly predicts cyberbullying.A significant cyber-victim-cyberbully cycle was observed. This study investigated the extent of young adults' (N=393; 17-30years old) experience of cyberbullying, from the perspectives of cyberbullies and cyber-victims using an online questionnaire survey. The overall prevalence rate shows cyberbullying is still present after the schooling years. No significant gender differences were noted, however females outnumbered males as cyberbullies and cyber-victims. Overall no significant differences were noted for age, but younger participants were found to engage more in cyberbullying activities (i.e. victims and perpetrators) than the older participants. Significant differences were noted for Internet frequency with those spending 2-5h online daily reported being more victimized and engage in cyberbullying than those who spend less than an hour daily. Internet frequency was also found to significantly predict cyber-victimization and cyberbullying, indicating that as the time spent on Internet increases, so does the chances to be bullied and to bully someone. Finally, a positive significant association was observed between cyber-victims and cyberbullies indicating that there is a tendency for cyber-victims to become cyberbullies, and vice versa. Overall it can be concluded that cyberbullying incidences are still taking place, even though they are not as rampant as observed among the younger users.

Stemming and lemmatization: A comparison of retrieval performances

Abstract: The current study proposes to compare document retrieval precision performances based on language modeling techniques, particularly stemming and lemmatization. Stemming is a procedure to reduce all words with the same stem to a common form whereas lemmatization removes inflectional endings and returns the base or dictionary form of a word. Comparisons were also made between these two techniques with a baseline ranking algorithm (i.e. with no language processing). A search engine was developed and the algorithms were tested based on a test collection. Both mean average precisions and histograms indicate stemming and lemmatization to outperform the baseline algorithm. As for the language modeling techniques, lemmatization produced better precision compared to stemming, however the differences are insignificant. Overall the findings suggest that language modeling techniques improves document retrieval, with lemmatization technique producing the best result.

Improving cyberbullying detection using Twitter users’ psychological features and machine learning

Abstract: Empirical evidences linking users’ psychological features such as personality traits and cybercrimes such as cyberbullying are many. This study deals with automatic cyberbullying detection mechanism tapping into Twitter users’ psychological features including personalities, sentiment and emotion. User personalities were determined using Big Five and Dark Triad models, whereas machine learning classifiers namely, Naive Bayes, Random Forest and J48 were used to classify the tweets into one of four categories: bully, aggressor, spammer and normal. The Twitter dataset contained 5453 tweets gathered using the hashtag #Gamergate, and manually annotated by human experts. Selected Twitter-based features namely text, user and network-based features were used as the baseline algorithm. Results show that cyberbullying detection improved when personalities and sentiments were used, however, a similar effect was not observed for emotion. A further analysis on the personalities revealed extraversion, agreeableness, neuroticism and psychopathy to have greater impacts in detecting online bullying compared to other traits. Key features were identified using the dimension reduction technique, and integrated into a single model, which produced the best detection accuracy. The paper describes suggestions and recommendations as to how the findings can be applied to mitigate cyberbullying.

Malaysian Facebookers: Motives and addictive behaviours unraveled

Abstract: Malaysians were reported to have the most number of Facebook friends, spend more time on Facebook and might be addicted to Facebook as well. This paper explored Facebook usage pattern, motivations and psychological/behavioural factors affecting the users. A focus group study was first conducted to explore motives to use Facebook and symptoms related to excessive Facebook usage. The themes emerging from this were then used in addition to Uses and Gratifications theory and Brown's Addiction framework to further explore Facebook usage pattern, motivations and behavioural issues among a large group of students. Results show that Malaysian students use Facebook actively, similar to other studies done worldwide. Factor analyses yielded five motives to use Facebook: Social Networking, Psychological Benefits, Entertainment, Self Presentation and Skill Enhancement. As for the behavioural symptoms, Salience, Loss of Control, Withdrawal and Relapse and Reinstatement emerged as the four main symptoms. These results show that in general Malaysian students use Facebook for similar motives as reported in literature. However, it is interesting to note that they also exhibited behavioural symptoms, such as Salience, Loss of Control, Withdrawal and Relapse and Reinstatement due to excessive Facebook usage.

Online Social Network Site Addiction: A Comprehensive Review

Abstract: Research into online social network site (SNS) addiction (i.e., excessive and compulsive online social networking) has expanded over the last years. This paper aims to give a review of this research. Although not formally recognized as a diagnosis, SNS addiction shares many similarities with those of other addictions, including tolerance, withdrawal, conflict, salience, relapse, and mood modification. Several screening instruments to identify SNS addicts have been developed—approaching the phenomenon in various ways, disclosing a conceptual and empirical obscurity in this field. Theoretical and empirical models suggest that SNS addiction is molded by several factors; including dispositional, sociocultural, and behavioral reinforcement. Also, empirical findings generally unveil that SNS addiction is related to impaired health and well-being. There has been little, if any, empirical testing of prevention or treatment for this behavioral addiction, although certain self-help strategies, therapies, and interventions have been proposed.

The uses and abuses of Facebook: A review of Facebook addiction.

Abstract: Background and aims: Recent research suggests that use of social networking sites can be addictive for some individuals. Due to the link between motivations for media use and the development of addiction, this systematic review examines Facebook-related uses and gratifications research and Facebook addiction research. Method: Searches of three large academic databases revealed 24 studies examining the uses and gratifications of Facebook, and nine studies of Facebook addiction. Results: Comparison of uses and gratifications research reveals that the most popular motives for Facebook use are relationship maintenance, passing time, entertainment, and companionship. These motivations may be related to Facebook addiction through use that is habitual, excessive, or motivated by a desire for mood alteration. Examination of Facebook addiction research indicates that Facebook use can become habitual or excessive, and some addicts use the site to escape from negative moods. However, examination of Facebook addiction measures highlights inconsistency in the field. Discussion: There is some evidence to support the argument that uses and gratifications of Facebook are linked with Facebook addiction. Furthermore, it appears as if the social skill model of addiction may explain Facebook addiction, but inconsistency in the measurement of this condition limits the ability to provide conclusive arguments. Conclusions: This paper recommends that further research be performed to establish the links between uses and gratifications and Facebook addiction. Furthermore, in order to enhance the construct validity of Facebook addiction, researchers should take a more systematic approach to assessment.

Seven Principles for Good Practice in Undergraduate Education: Faculty Inventory. Institutional Inventory.

Abstract: Arthur Chickering is Distinguished Professor of Higher Education at Memphis State University. On leave from the Directorship of the Center for the Study of Higher Education at Memphis State, he is Visiting Professor at George Mason University. Zelda Gamson is a sociologist who holds appointments at the John W. McCormack Institute of Public Affairs at the University of Massachusetts-Boston and in the Center for the Study of Higher and Postsecondary Education at the University of Michigan.