Chasing the Chatbots: Directions for Interaction and Design Research

Big tech-players have been successful in pushing the chatbots forward. Investments in the technology are growing fast, as well as the number of users and applications available. Instead of driving investments towards a successful diffusion of the technology, user-centred studies are currently chasing the popularity of chatbots. A literature analysis evidences how recent this research topic is, and the predominance of technical challenges rather than understanding users’ perceptions, expectations and contexts of use. Looking for answers to interaction and design questions raised in 2007, when the presence of clever computers in everyday life had been predicted for the year 2020, this paper presents a panorama of the recent literature, revealing gaps and pointing directions for further user-centred research

Distance-Aware Selective Online Query Processing Over Large Distributed Graphs

Performing online selective queries against graphs is a challenging problem due to the unbounded nature of graph queries which leads to poor computation locality. It becomes even difficult when a graph is too large to be fit in the memory. Although there have been emerging efforts on managing large graphs in a distributed and parallel setting, e.g., Pregel, HaLoop and etc, these computing frameworks are designed from the perspective of scalability instead of the query efficiency. In this work, we present our solution methodology for online selective graph queries based on the shortest path distance semantic, which finds various applications in practice. The essential intuition is to build a distance-aware index for online distance-based query processing and to eliminate redundant graph traversal as much as possible. We discuss how the solution can be applied to two types of research problems, distance join and vertex set bonding, which are distance-based graph pattern discovery and finding the structure-wise bonding of vertices, respectively

Social media metrics for new research evaluation

This chapter approaches, both from a theoretical and practical perspective, the most important principles and conceptual frameworks that can be considered in the application of social media metrics for scientific evaluation. We propose conceptually valid uses for social media metrics in research evaluation. The chapter discusses frameworks and uses of these metrics as well as principles and recommendations for the consideration and application of current (and potentially new) metrics in research evaluation.Comment: Forthcoming in Glanzel, W., Moed, H.F., Schmoch U., Thelwall, M. (2018). Springer Handbook of Science and Technology Indicators. Springe

Social media metrics for new research evaluation

Merit, Expertise and Measuremen

Design for Creating, Uploading and Sharing User Generated Content

The power of users playing the roles of authors and editors is undeniable these days [1]. New media, not only the Internet, are enabling people to become active users related to content production and sharing, and in co-creation of User Generated Content (UGC). In particular younger users and heavy users of Internet use networked applications to create and share content [1]. There is a need for UGC applications targeting a broader market, including older users and average Internet users. Today, the knowledge in designing and building for co-creation in networked media is still rather weak. The lack of information about UGC characteristics makes it difficult to expect what kind and amount of content will be produced, and to understand and interpret the reasons why users and user communities arise or fail. A significant effort is currently made by the HCI community in order to support active user involvement into the design and evaluation of networked applications [6]. Non-professional users are encouraged to become active producers and designers themselves [1]. However, there is still the need to explore how to apply and further extend these approaches and methods to better understand, design for and evaluate UGC applications. This SIG will contribute to this discussion by actively involving the audience in UGC creation.status: publishe

Why People Use Chatbots

There is a growing interest in chatbots, which are machine agents serving as natural language user interfaces for data and service providers. However, no studies have empirically investigated people’s motivations for using chatbots. In this study, an online questionnaire asked chatbot users (N = 146, aged 16–55 years) from the US to report their reasons for using chatbots. The study identifies key motivational factors driving chatbot use. The most frequently reported motivational factor is “productivity”; chatbots help users to obtain timely and efficient assistance or information. Chatbot users also reported motivations pertaining to entertainment, social and relational factors, and curiosity about what they view as a novel phenomenon. The findings are discussed in terms of the uses and gratifications theory, and they provide insight into why people choose to interact with automated agents online. The findings can help developers facilitate better human–chatbot interaction experiences in the future. Possible design guidelines are suggested, reflecting different chatbot user motivations.acceptedVersio

All Citizens are the Same, Aren’t They? – Developing an E-government User Typology

Part 6: Open GovernmentInternational audienceTaking a closer look at current research on e-government diffusion shows that most studies or conceptual works deal with citizens as one broad mass that is not further described or divided into smaller subgroups. Such efforts are mainly limited to the digital divide discourse and distinguish at most between haves and have-nots or younger and older parts of the population. Understanding why and how citizens use public online services also requires an understanding of how different segments of the population react to IT in general as well as to e-government in particular. To date, no meaningful attempts to develop such an e-government user typology have been undertaken. Therefore, the study at hand aims at developing a user typology for the e-government context. To this end, we chose an explorative design and conducted a qualitative interview study in Germany in 2016 with 18 respondents from all age groups. We qualitatively analyzed the sample regarding usage behavior, variety of use, and e-government specific uses and perceptions. Our research reveals six user types differing in quality and quantity of use with regard to internet-based technologies in general and e-government services in particular. Understanding how different populations perceive e-government and contextualizing their behavior can help explaining why some citizens are making advanced use of e-government while others widely ignore these services