Event Organization 101: Understanding Latent Factors of Event Popularity

The problem of understanding people's participation in real-world events has been a subject of active research and can offer valuable insights for human behavior analysis and event-related recommendation/advertisement. In this work, we study the latent factors for determining event popularity using large-scale datasets collected from the popular Meetup.com EBSN in three major cities around the world. We have conducted modeling analysis of four contextual factors (spatial, group, temporal, and semantic), and also developed a group-based social influence propagation network to model group-specific influences on events. By combining the Contextual features And Social Influence NetwOrk, our integrated prediction framework CASINO can capture the diverse influential factors of event participation and can be used by event organizers to predict/improve the popularity of their events. Evaluations demonstrate that our CASINO framework achieves high prediction accuracy with contributions from all the latent features we capture.Comment: International AAAI Conference on Web and Social Media (ICWSM) 2017 https://www.aaai.org/ocs/index.php/ICWSM/ICWSM17/paper/view/1557

Creating a theoretical framework for platforms strategies from launch to growth

Many platforms have gained their way into consumers daily lives by shifting values and expectations, increasing ability to self-express oneself, satisfying new needs while expanding markets and creating new industries. This is what platform revolution means, yet the strategies and logic behind platforms remain much unknown. The current literature identifies as the key strategic variables for platforms to be user acquisition, standalone value, credibility, profitability, design and openness. However, these discussions don’t give clear guidance on how to implement or prioritize these variables according different platform types. While the current understanding of strategic differences and how to combine tactics and variables towards each platform type is forming, so is classifying and separating platform types from each other. While the two papers have classified platform types their conclusions differed staying unconfirmed. Therefore, the purpose of this study is to determine platform businesses strategies and to create a theoretical framework reflecting it while answering to the research question: what strategies platforms apply as they go in business and how they attempt to grow? The empirical part of this study is aimed at developing a theoretical framework representing the strategic decisions made by platforms. It was conducted as an in-depth multi case study by interviewing 14 platform as well as testing 70 platforms’ user experience. Based on these two data sets a theoretical framework was formed that is applicable within the Western world. Consequently, the theoretical framework representing the key finding of this thesis separates 12 unique platform strategies for launching a platform business across three platform types identified as an e-marketplace, software as a service and social networking sites. Thus, stating that there are at least 12 unique platform strategies that organizations follow. The framework guides what kind of MVP, key target group and social factors each 12 platform strategy types can utilize and the boundaries each type has. It also gives descriptions on all 12 platform strategies and minimum example of four businesses that follow that strategy. Furthermore, the thesis discusses multiple vertical and horizontal expansion strategies that each platform strategy type can apply when attracting further growth towards itself and the factors that need to be considered simultaneously. The contributions done towards platform strategies, SaaS and SNS by the framework are ground-breaking and significant as they create new unique knowledge while invalidating and correcting two past attempts to classify and group platforms. However, this thesis contributes also to the conceptual understanding of the platform types, how different variables are interlinked to one another and to the framework. It also specifies the current understanding of e-marketplace platform strategies

Navigation System for Foreign Tourists in Japan

The present study aimed to design, develop, operate and evaluate a sightseeing navigation system in order to support foreign tourists’ efficient acquisition of sightseeing spot information in Japanese urban tourist areas, about which a variety of information is transmitted, by enabling information to be accumulated, shared and recommended. The system was developed by integrating Web-GIS (Geographic Information Systems), SNS (Social Networking Services) as well as the recommendation system into a single system. The system used the non-language information such as signs, marks and pictograms in addition to English information, and displayed sightseeing spot information and conduct navigation on 2D and 3D digital maps of the Web-GIS. Additionally, the system was operated for two weeks in the central part of Yokohama city in Kanagawa Prefecture, Japan, and the total number of users was 54. Based on the results of the web questionnaire survey, all of the specific functions are highly evaluated, and the usefulness of the system when sightseeing was excellent. From the results of the access analysis of users’ log data, it is evident that it can be said that the system was mainly used before sightseeing and users confirm their favorite sightseeing spots and made their tour planning in advance, using 2D and 3D digital maps

Reducing Third Parties in the Network through Client-Side Intelligence

The end-to-end argument describes the communication between a client and server using functionality that is located at the end points of a distributed system. From a security and privacy perspective, clients only need to trust the server they are trying to reach instead of intermediate system nodes and other third-party entities. Clients accessing the Internet today and more specifically the World Wide Web have to interact with a plethora of network entities for name resolution, traffic routing and content delivery. While individual communications with those entities may some times be end to end, from the user's perspective they are intermediaries the user has to trust in order to access the website behind a domain name. This complex interaction lacks transparency and control and expands the attack surface beyond the server clients are trying to reach directly. In this dissertation, we develop a set of novel design principles and architectures to reduce the number of third-party services and networks a client's traffic is exposed to when browsing the web. Our proposals bring additional intelligence to the client and can be adopted without changes to the third parties. Websites can include content, such as images and iframes, located on third-party servers. Browsers loading an HTML page will contact these additional servers to satisfy external content dependencies. Such interaction has privacy implications because it includes context related to the user's browsing history. For example, the widespread adoption of "social plugins" enables the respective social networking services to track a growing part of its members' online activity. These plugins are commonly implemented as HTML iframes originating from the domain of the respective social network. They are embedded in sites users might visit, for instance to read the news or do shopping. Facebook's Like button is an example of a social plugin. While one could prevent the browser from connecting to third-party servers, it would break existing functionality and thus be unlikely to be widely adopted. We propose a novel design for privacy-preserving social plugins that decouples the retrieval of user-specific content from the loading of third-party content. Our approach can be adopted by web browsers without the need for server-side changes. Our design has the benefit of avoiding the transmission of user-identifying information to the third-party server while preserving the original functionality of the plugins. In addition, we propose an architecture which reduces the networks involved when routing traffic to a website. Users then have to trust fewer organizations with their traffic. Such trust is necessary today because for example we observe that only 30% of popular web servers offer HTTPS. At the same time there is evidence that network adversaries carry out active and passive attacks against users. We argue that if end-to-end security with a server is not available the next best thing is a secure link to a network that is close to the server and will act as a gateway. Our approach identifies network vantage points in the cloud, enables a client to establish secure tunnels to them and intelligently routes traffic based on its destination. The proliferation of infrastructure-as-a-service platforms makes it practical for users to benefit from the cloud. We determine that our architecture is practical because our proposed use of the cloud aligns with existing ways end-user devices leverage it today. Users control both endpoints of the tunnel and do not depend on the cooperation of individual websites. We are thus able to eliminate third-party networks for 20% of popular web servers, reduce network paths to 1 hop for an additional 20% and shorten the rest. We hypothesize that user privacy on the web can be improved in terms of transparency and control by reducing the systems and services that are indirectly and automatically involved. We also hypothesize that such reduction can be achieved unilaterally through client-side initiatives and without affecting the operation of individual websites

Recommendations based on social links

The goal of this chapter is to give an overview of recent works on the development of social link-based recommender systems and to offer insights on related issues, as well as future directions for research. Among several kinds of social recommendations, this chapter focuses on recommendations, which are based on users’ self-defined (i.e., explicit) social links and suggest items, rather than people of interest. The chapter starts by reviewing the needs for social link-based recommendations and studies that explain the viability of social networks as useful information sources. Following that, the core part of the chapter dissects and examines modern research on social link-based recommendations along several dimensions. It concludes with a discussion of several important issues and future directions for social link-based recommendation research