Social Media Adoption Among University Instructors In Saudi Arabia

There is an orientation from the government of Saudi Arabia toward social media in general. The government of Saudi Arabia considers the significance of social media in educating the Saudi community. The Saudi Ministry of Education founded the National Center for E- Learning and Distance Learning (NCeL) because it considered the importance of e-learning and distance learning for higher education (he.moe.gov.sa). NCeL supports and rewards university instructors to integrate social media in the learning process (award.elc.edu.sa). Several studies proved the significance of social media with Saudi higher education students (Alkhalifa, 2008; Salem and Alghamdi, 2011; Almadhouni, 2011). Moreover, Saudi students indicated positive attitudes toward social media in their learning and would prefer attending classes that university instructors use social media (Aifan, 2015). However, the adoption of social media for teaching students by university instructors in Saudi Arabia is unclear. A questionnaire was built based on Rogers’ Diffusion of Innovations theory for the study purpose. 387 university instructors from all of the 28 Saudi public universities responded to the questionnaire. 47.5% of the participants were male university instructors, while 51.7% were female university instructors. .8% of the participants preferred not to disclose their gender. 130 47.8% of the participants were 35 years old or below, 29.2% were between 36-45 years old, and 17.8% were 46years old and more. The results of this cross-sectional descriptive study that the Knowledge stage was the highest stage that university instructors have identified themselves with the stages of the innovation-decision, followed by Decision stage, Persuasion stage, Confirmation stage, and Implementation stage. The findings of this study imply that the perceived relative advantage and compatibility of using social media in teaching students may increase university instructors (in general and for all ages) future adoption decision of using social media in teaching students. Moreover, the findings of this study imply that the perceived relative advantage of using social media in teaching students may increase female university instructors’ future adoption decision of using social media in teaching students, whereas the perceived compatibility of using social media in teaching students may increase male university instructors’ future adoption decision of using social media in teaching students. Finally, the findings of this study imply that the perceived complexity, trialability, and observability of using social media in teaching students may have no influence on increasing university instructors’ future adoption decision of using social media in teaching students

Tracing the German Centennial Flood in the Stream of Tweets: First Lessons Learned

Social microblogging services such as Twitter result in massive streams of georeferenced messages and geolocated status updates. This real-time source of information is invaluable for many application areas, in particular for disaster detection and response scenarios. Consequently, a considerable number of works has dealt with issues of their acquisition, analysis and visualization. Most of these works not only assume an appropriate percentage of georeferenced messages that allows for detecting relevant events for a specific region and time frame, but also that these geolocations are reasonably correct in representing places and times of the underlying spatio-temporal situation. In this paper, we review these two key assumption based on the results of applying a visual analytics approach to a dataset of georeferenced Tweets from Germany over eight months witnessing several large-scale flooding situations throughout the country. Our results con rm the potential of Twitter as a distributed 'social sensor' but at the same time highlight some caveats in interpreting immediate results. To overcome these limits we explore incorporating evidence from other data sources including further social media and mobile phone network metrics to detect, confirm and refine events with respect to location and time. We summarize the lessons learned from our initial analysis by proposing recommendations and outline possible future work directions

The Role of Social CRM in Social Information Systems: Findings from Four Case Studies

Social Information Systems (SIS) are larger systems of open and voluntary collaboration between involved parties and based on Social Media. Recent research about SIS describes characteristics, constituting elements and research streams. However, detailed analysis about the effects and system design of SIS are still limited. This paper investigates the concept of SIS from the perspective of Customer Relationship Management (CRM). It illustrates similarities and differences between SIS and Social CRM implementations by drawing on existing research and the examination of four cases studies. The findings show benefits and requirements for the adoption of SIS in the field of CRM. On one hand, SIS provide new means for CRM by fostering the creation and nurturing of relationships between business and the market. On the other hand, for realizing these opportunities companies need to further integrate Social Media, CRM and Social CRM from an inside-out and outside-in perspective

Emergent Technology And The Millennial Generation: Examining The Perceptions Of Students And Implications For Instruction In Higher Education

The objective of this research was to determine students‘ perception of technology in higher education. The study participants were recruited from two institutions of higher learning: a small private women‘s historically black college (School A) consisting of about 740 students and a large public historically black university (School B) consisting of about 10,000 students, both located in a single mid-sized metropolitan area in the southeastern United States

Microbloggers’ motivations in participatory journalism: A cross-cultural study of America and China

This phenomenological study focuses on the motivations of participatory journalists contributing on microblogs such as Twitter and Weibo. Although online user behavior and motivations have been studied before, few studies have examined motivations of participatory journalists from their own perspective. Moreover, this study is one of the few to explore participatory journalists across different cultures (U.S. and China). The author conducted a total of 13 in-depth interviews with participatory journalists on microblogs from both countries and used a qualitative analysis method to identify the themes and patterns that emerged. Motivations such as earning respect, technology early adoption, self-expression, relationship building, self-enhancement, branding and image building, and financial gain were discussed. De-motivational factors such as time constraints and self-censorship were presented. Motivational differences between the two groups of participants, including what the microblog account represents and the role of participatory journalists, were explained by cultural differences collectivism versus individualism and power distance. Limitations and future research were also discussed

Doctor of Philosophy

dissertationDue to the popularity of Web 2.0 and Social Media in the last decade, the percolation of user generated content (UGC) has rapidly increased. In the financial realm, this results in the emergence of virtual investing communities (VIC) to the investing public. There is an on-going debate among scholars and practitioners on whether such UGC contain valuable investing information or mainly noise. I investigate two major studies in my dissertation. First I examine the relationship between peer influence and information quality in the context of individual characteristics in stock microblogging. Surprisingly, I discover that the set of individual characteristics that relate to peer influence is not synonymous with those that relate to high information quality. In relating to information quality, influentials who are frequently mentioned by peers due to their name value are likely to possess higher information quality while those who are better at diffusing information via retweets are likely to associate with lower information quality. Second I propose a study to explore predictability of stock microblog dimensions and features over stock price directional movements using data mining classification techniques. I find that author-ticker-day dimension produces the highest predictive accuracy inferring that this dimension is able to capture both relevant author and ticker information as compared to author-day and ticker-day. In addition to these two studies, I also explore two topics: network structure of co-tweeted tickers and sentiment annotation via crowdsourcing. I do this in order to understand and uncover new features as well as new outcome indicators with the objective of improving predictive accuracy of the classification or saliency of the explanatory models. My dissertation work extends the frontier in understanding the relationship between financial UGC, specifically stock microblogging with relevant phenomena as well as predictive outcomes

Going Social: Tapping Into Social Media for Nonprofit Success

Designed for nonprofit professionals as a means to discover and deploy social media programs that further an organization's mission

Prototype/topic based Clustering Method for Weblogs

[EN] In the last 10 years, the information generated on weblog sites has increased exponentially, resulting in a clear need for intelligent approaches to analyse and organise this massive amount of information. In this work, we present a methodology to cluster weblog posts according to the topics discussed therein, which we derive by text analysis. We have called the methodology Prototype/Topic Based Clustering, an approach which is based on a generative probabilistic model in conjunction with a Self-Term Expansion methodology. The usage of the Self-Term Expansion methodology is to improve the representation of the data and the generative probabilistic model is employed to identify relevant topics discussed in the weblogs. We have modified the generative probabilistic model in order to exploit predefined initialisations of the model and have performed our experiments in narrow and wide domain subsets. The results of our approach have demonstrated a considerable improvement over the pre-defined baseline and alternative state of the art approaches, achieving an improvement of up to 20% in many cases. The experiments were performed on both narrow and wide domain datasets, with the latter showing better improvement. However in both cases, our results outperformed the baseline and state of the art algorithms.The work of the third author was carried out in the framework of the WIQ-EI IRSES project (Grant No. 269180) within the FP7 Marie Curie, the DIANA APPLICATIONS Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) project and the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems.Perez-Tellez, F.; Cardiff, J.; Rosso, P.; Pinto Avendaño, DE. (2016). Prototype/topic based Clustering Method for Weblogs. Intelligent Data Analysis. 20(1):47-65. https://doi.org/10.3233/IDA-150793S476520