IADIS INTERNATIONAL JOURNAL ON WWW/INTERNET

19-33

Authors: Ashraf Khalil, Aishah Khan, Tasbeeh Fatima Raza and Salam Abdallah

Emergence of new features on social media platforms have become a daily occurrence. Stories, live videos, memories and various other emerging features are a crucial part of most of the popular social media platforms. Through this study, we conduct a qualitative assessment of user adaptation to these revolutionizing social media features. The aim of this study is to understand user preferences based on platforms, their adaptability and usage of these features. This study derives conclusions based on a semi-structured interview conducted on 18 users in their early twenties in the UAE. The study derives conclusions on changes in user behavior on Facebook, user strategies for managing different audiences and content across social media platforms, views on cross-linking and cross-sharing of social platforms and using social media as a common portal to keep track of daily happenings. The study finds that users treat social media platforms distinctly while tending to share different contents on each platform depending on the nature of the content and the audience of each platform.

50-65

Authors: Isa Inuwa-Dutse, Bello Shehu Bello and Ioannis Korkontzelos

The rise in the number of automated or bot accounts on Twitter engaging in manipulative behaviour is of great concern to studies using social media as a primary data source. Many strategies have been proposed and implemented, however, the sophistication and rate of deployment of bot accounts is increasing rapidly. This impedes and limits the capabilities of detecting bot strategies. Various features broadly related to account profiles, tweet content, network and temporal patterns have been utilised in detection systems. Tweet content has been proven instrumental in this process, but limited to the terms and entities occurring. Given a set of tweets with no obvious pattern, can we distinguish contents produced by social bots from those of humans? What constitutes engagement on Twitter and how can we measure the intensity of engagement? Can we distinguish between bot and human accounts based on engagement intensity? These are important questions whose answer will improve how detection systems operate to combat malicious activities by effectively distinguishing between human and social bot accounts on Twitter. This study attempts to answer these questions by analysing the engagement intensity and lexical richness of tweets produced by human and social bot accounts using large, diverse datasets. Our results show a clear margin between the two classes in terms of engagement intensity and lexical richness. We found that it is extremely rare for a social bot to engage meaningfully with other users and that lexical features significantly improve the performance of classifying both account types. These are important dimensions to explore toward improving the effectiveness of detection systems in combating the menace of social bot accounts on Twitter.

80-94

Authors: Angela Martin, Corentin Canu, Camille Jean and Gabrièle Breda

The main focus of this study is to provide a new framework for business model design by using complex system modelling. The tool offers both entrepreneurs and investors a comprehensive view of value streams by comparing different business models based on the economic shared value creation during the go to market process.

1-18

Authors: Syed Tauhid Zuhori and James Miller

Understanding user requirements based on their interactions with a website is becoming increasingly important. Hence, in this paper, a novel real-time navigation-support system is discussed. This system builds a personalized browsing assistant based on the current user request submitted to a web server. The process involves developing a behavior model using a Discrete Time Markov Chain (DTMCs) inference process. This is then used to monitor user activities, and thereafter suggest “where to go next”. Finally, it updates the model in real time using a Markovian Decision Process (MDP). To evaluate the system, we provide a user study, case studies and conduct experiments on two datasets to verify the effectiveness of our proposed system.

26-41

Authors: Francisco Javier Delgado-Cepeda

Quantum information is an emerging area of research which is growing rapidly and which is expecting to have a deep impact in the speed of information processing, storage and security. With only few decades of development, that trend has been highlighted as a remarkable economic focus for the development. Despite, this research area is barely identified in the general society as a source of opportunities for the personal development. The academic development for the most universities reacts slowly to these changes. Their educative programs are normally static with only some late adaptations to the newest technology or knowledge advancement, incorporating them in a limited strength. This research area, normally thought by the common people as proper for physicists, it is really open for lots of disciplines in nowadays. Any area with complex problems unable to be attained by classical computing could technically to be involved in this research trend. Thus, alternative new professional areas are emerging without be sufficiently visible for the universities in order to move the most traditional areas of education. Thus, in the next years, some emergent areas could be eclipsed in terms of human resources. In this arena, blended learning could contribute to provide novel educative contents as an alternative or complementary education to the main professional area selected. While, the blended learning approach is being developed to reach the most sectors of population with professional and university education. Strategies of blended learning are considered remarkable either for formal education as well specialized education to disseminate new trends not included in the traditional syllabus but important for the professional development of students. Because that is the case for Quantum information and Quantum computation areas having an explosive development just in the last decade, this work describes the outcomes around a blended learning initiative in the form of an educative suite for those areas with a multidisciplinary approach containing courses oriented to arrive into the formal research. Still, they are departing from the scientific divulgation until research collaboration going on through the formal learning. Suite was conceptualized with a multilevel approach to attract and to involve students from high school until graduate level.

42-55

Authors: Heritiana Ranaivoson and Simon Delaere

This paper analyses how innovation and business models are related in the case of immersive audiovisual services, with a focus on three distribution platforms: HTC’s Viveport, Facebook’s Oculus Home and Google’s YouTube VR. To do so, it first briefly discusses the issues at stake in terms of media innovation, in particular the fact that content innovation is often neglected or misunderstood. After briefly summarizing relevant previous work, it then applies the Business Model Matrix (Ballon, 2009) to these three cases. In particular, the cases are compared in terms of vertical integration, customer ownership, interoperability, revenue model, positioning, user involvement, and the role of content innovation. The paper concludes with a comparison of the cases. It expands the rapidly growing literature on media innovation by using a business model methodology, providing the first instance of an in-depth, structured comparison of immersive audiovisual services from a business point of view. It aims to fill a knowledge gap by dealing with a sector almost ignored by business or economic academic literature.

56-69

Authors: Jukka Vuorinen, Aki Koivula and Ilkka Koiranen

Internet related personal communication has increased significantly in the course of recent years. Simultaneously, the possibility of sharing sensitive personal information has become a part of everyday life. Thus, the possibility of privacy violations and leaking of personal data has arisen. This paper analyzes the extent to which Internet users trust that the privacy of their private messages is protected and upheld in web-based messaging services such as Facebook Messenger and WhatsApp. The paper examines how users’ trust in other people (social trust) and trust in institutional actors (such as the parliamentary system and police) predict a high probability to trust that their private and confidential messages are not disclosed. The analysis is conducted based on data (n=1648) that was gathered through a nationwide survey in Finland. Results show that both high social trust and institutional trust are associated with high trust in the confidentiality and privacy of messages that are sent through messaging services on the web. Demographic factors did not have a remarkable effect on how trusting users are. Finally, a decomposition analysis shows that social trust is the strongest predictor even when institutional trust and demographic factors are controlled for.

70-84

Authors: Kungela Mzuku and Jean-Paul Van Belle

This article presents a qualitative research study which explores the emergent phenomenon of Data Philanthropy in South African corporate organisations. The main research objective is to investigate the corporate attitudes towards Data Philanthropy in the South African banking, retail and telecommunications industries. In particular, the study examines of the willingness, preparedness and concerns of corporations in respect of using their data and supporting data analytical technologies for social good, their chosen level of engagement in corporate social responsibility. Also investigated was and their willingness to change their current engagement to one that requires more efforts and tools to implement. The study includes a review which exposes gaps in literature that the research analysis and discussion will aim to uncover. The study used an inductive approach using thematic analysis. Four main organising themes are used to analyse the data which was collected through interviews namely Corporate Social Responsibility, Willingness, Preparedness and Concerns. A remarkable diversity in detailed sub-themes was uncovered for each of the main themes.