Understanding the bi-directional message diffusion mechanism in the context of IT trends and current social issues

2021 | Information & Management | Citations: 0

Authors: Park, Ji Hye; Moon, Jae Yun; Hong, Se-Joon

Abstract: Amid the skyrocketing increase in social media content, understanding the inform ... Expand

Abstract: Amid the skyrocketing increase in social media content, understanding the information-sharing mechanism is crucial. We analyze Twitter messages on recent public issues and IT trends to examine the network’s bidirectional message diffusion patterns through incoming and outgoing ties, based on the users’ retweeting and mentioning behavior toward one another. We find context-based patterns. This study shows that regarding IT trends, the use of the “like” feature significantly related to users’ influence, where outgoing ties had a greater mediating influence than incoming ties. During COVID-19, users prioritized obtaining reliable information. Our findings contribute toward developing diffusion mechanisms and social media strategies. Collapse

Topics: Twitter internet of things mobile system artificial intelligence social media

Methods: descriptive statistic computational algorithm network analysis statistical hypothesis test correlation analysis

Theories: social exchange theory

A storyteller's guide to problem-based learning for information systems management education

2019 | Information Systems Journal | Citations: 0

Authors: Hull, David M.; Lowry, Paul Benjamin; Gaskin, James E.; Mirkovski, Kristijan

Abstract: More than a decade ago, evidence-based recommendations emerged regarding what st ... Expand

Abstract: More than a decade ago, evidence-based recommendations emerged regarding what students of information systems (IS) management education should learn and how should they learn it. Although these recommendations for how IS management should be taught remain valid, they need to be updated to account for recent advances in technologies that enable multimedia learning. Promoters of such technologies promise enhanced cognitive and behavioural outcomes, but this promise remains unreached, reflecting the underdeveloped multimedia-enabled learning literature. To help attain this promise and rejuvenate the literature of multimedia learning, we offer a roadmap for new areas of research that would inform the design and use of a novel form of multimedia materials: narrative animated videos (NAVs). NAVs represent a form of self-determined learning that features immersive, story-based content. We argue that their use will intrinsically motivate users to process the materials to completion, thereby enhancing cognitive and behavioural outcomes, and thus catalysing the effectiveness of the team-based learning and self-regulated learning modes for problem-based learning (PBL) delivery of IS management education. This compelling roadmap corresponds to meaningful IS research because it centres on a topic that the IS literature has long examined—the role of user motivation—and because its theoretical contributions invite specific paths of research for informing the design of the PBL delivery of IS management education within an information systems artefact. Collapse

Topics: IS management intrinsic motivation sensemaking problem solving phishing

Methods: theory development design artifact literature study

Theories: hedonic motivation system adoption model information systems theory multi motive information systems continuance model motivation theory

Nonlinear Negotiation Approaches for Complex-Network Optimization: A Study Inspired by Wi-Fi Channel Assignment

2019 | Group Decision and Negotiation | Citations: 0

Authors: Marsa-Maestre, Ivan; de la Hoz, Enrique; Gimenez-Guzman, Jose Manuel; Orden, David; Klein, Mark

Abstract: At the present time, Wi-Fi networks are everywhere. They operate in unlicensed r ... Expand

Abstract: At the present time, Wi-Fi networks are everywhere. They operate in unlicensed radio-frequency spectrum bands (divided in channels), which are highly congested. The purpose of this paper is to tackle the problem of channel assignment in Wi-Fi networks. To this end, we have modeled the networks as multilayer graphs, in a way that frequency channel assignment becomes a graph coloring problem. For a high number and variety of scenarios, we have solved the problem with two different automated negotiation techniques: a hill-climbing mediated negotiation and a simulated annealing mediated negotiation. As an upper bound reference for the performance of these two techniques, we have also solved the problem using a particle swarm optimizer. Results show that the annealer negotiator behaves as the best choice because it is able to obtain even better results than the particle swarm optimizer in the most complex scenarios under study, with running times one order of magnitude below. Moreover, we study how different properties of the network layout affect to the performance gain that the annealer is able to obtain with respect to the particle swarm optimizer. Finally, we show how the different strategic behavior of the participants affects the results. Collapse

Topics: wireless LAN economic surplus IS economics local area network

Methods: experiment optimization model computational algorithm discrete optimization cluster analysis

Theories: graph theory

Academic paper recommender system using multilevel simultaneous citation networks

2018 | Decision Support Systems | Citations: 10

Authors: Son, Jieun; Kim, Seoung Bum

Abstract: Researchers typically need to filter several academic papers to find those relev ... Expand

Abstract: Researchers typically need to filter several academic papers to find those relevant to their research. This filtering is cumbersome and time-consuming because the number of published academic papers is growing exponentially. Some researchers have focused on developing better recommender systems for academic papers by using citation analysis and content analysis. Most traditional content analysis is implemented using a keyword matching process, and thus it cannot consider the semantic contexts of items. Further, citation analysis-based techniques rely on the number of links directly citing or being cited in a single-level network. Consequently, it may be difficult to recommend the appropriate papers when the paper of interest does not have enough citation information. To address these problems, we propose a recommendation system for academic papers that combines citation analysis and network analysis. The proposed method is based on multilevel citation networks that compare all the indirectly linked papers to the paper of interest to inspect the structural and semantic relationships among them. Thus, the proposed method tends to recommend informative and useful papers related to both the research topic and the academic theory. The comparison results based on real data showed that the proposed method outperformed the Google Scholar and SCOPUS algorithms. Collapse

Topics: recommender system Google+ search engine user satisfaction

Methods: co-citation analysis literature sample experiment computational algorithm network analysis

Android application classification and anomaly detection with graph-based permission patterns

2017 | Decision Support Systems | Citations: 0

Authors: Sokolova, Karina; Perez, Charles; Lemercier, Marc

Abstract: Android is one of the mobile market leaders, offering more than a million applic ... Expand

Abstract: Android is one of the mobile market leaders, offering more than a million applications on Google Play store. Google checks the application for known malware, but applications abusively collecting users' data and requiring access to sensitive services not related to functionalities are still present on the market. A permission system is a user-centric security solution against abusive applications and malware that has been unsuccessful: users are incapable of understanding and judging the permissions required by each application and often ignore on-installation warnings. State-of-the-art shows that the current permission system is inappropriate for end-users. However, Android permission lists do provide information about the application's behavior and may be suitable for automatic application analysis. Identifying key permissions for functionalities and expected permission requests can help leverage abnormal application behavior and provide a simpler risk warning for users. Applications with similar functionalities are grouped into categories on Google Play and this work therefore analyzes permission requests by category. In this study, we propose a methodology to characterize normal behavior for each category of applications, highlighting expected permission requests. The co-required permissions are modeled as a graph and the category patterns and central permissions are obtained using graph analysis metrics. The obtained patterns are evaluated by the performance of the application classification into categories that allow choosing the best graph metrics representing categories. Finally, this study proposes a privacy score and a risk warning threshold based on the best metrics. The efficiency of the proposed methodology was tested on a set of 9512 applications collected from Google Play and a set of malware. Collapse

Topics: Android privacy mobile application market malware digital distribution

Methods: machine learning computational algorithm graph analysis Bayesian analysis random forest classification

TWITTER AND THE POLITICAL LANDSCAPE – A GRAPH ANALYSIS OF GERMAN POLITICIANS

2016 | European Conference On Information Systems | Citations: 0

Authors: Baumann, Annika; Fabian, Benjamin; Lessmann, Stefan; Holzberg, Lars

Abstract: This paper examines the Twitter social graph of German politicians and political ... Expand

Abstract: This paper examines the Twitter social graph of German politicians and political parties during a time period not potentially biased by nearby elections. Based on a data set of 1,719 politicians across the entire political spectrum of this important country in the EU, two graphs are constructed, which also reflect relationships within and between parties: the follower graph, consisting of all followerfollowee relationships between German politicians, and the “mention graph”, which models direct references of politicians to their colleagues. Collapse

Topics: Twitter social media horizontal differentiation communication service infrastructure application programming interface

Methods: graph analysis case study cluster analysis descriptive statistic paired t-test