This product works well (for me): The impact of first-person singular pronouns on online review helpfulness

Can linguistic choices of reviewers, such as using first-person singular pronouns (FPSP), affect readers' perception of information helpfulness? When sharing their purchase and consumption experiences, online reviewers tend to excessively use FPSP to refer to themselves. However, the effect of this language choice on readers' perception of information value is unknown. Drawing on communication and psycholinguistic literatures, this research theoretically develops and empirically analyzes the effects of the use of FPSP on perceived review helpfulness. The empirical results, based on a sample of 41,656 reviews from Amazon.com, suggest that the use of these pronouns has a negative impact on the perceived helpfulness of online reviews. In addition, such effects are moderated by review attributes such as length, valence and affective content, being more prominent for shorter reviews, reviews with lower valence and higher level of affect

Mixing the reactive with the personal: Opportunities for end-user programming in personal information management

The transition of personal information management (PIM) tools off the desktop to the Web presents an opportunity to augment these tools with capabilities provided by the wealth of real-time information readily available. In this chapter, we describe a personal information assistance engine that lets end-users delegate to it various simple context- and activity-reactive tasks and reminders. Our system, Atomate, treats RSS/ATOM feeds from social networking and life-tracking sites as sensor streams, integrating information from such feeds into a simple unified RDF world model representing people, places and things and their time-varying states and activities. Combined with other information sources on the web, including the user's online calendar, web-based e-mail client, news feeds and messaging services, Atomate can be made to automatically carry out a variety of simple tasks for the user, ranging from context-aware filtering and messaging, to sharing and social coordination actions. Atomate's open architecture and world model easily accommodate new information sources and actions via the addition of feeds and web services. To make routine use of the system easy for non-programmers, Atomate provides a constrained-input natural language interface (CNLI) for behavior specification, and a direct-manipulation interface for inspecting and updating its world model

The Impact of Online Reviews on the Information Flows and Outcomes of Marketing Systems

Online reviews are changing the way that consumers shop and firms respond to consumer feedback. Viewed more broadly, online reviews are a type of information flow altering the functioning of marketing systems at the micro, meso, and macro levels. A systematic review of the past two decades of research shows great attention to the impact of online reviews on information flows, as well as the nuances of micro-and meso-level efficiency outcomes. However, there is scant consideration for the effectiveness related outcomes of online reviews (such as customer well-being, distributive justice, and externalities). Through a macromarketing lens, online reviews are an information flow with the potential to change well-being outcomes for all stake-holders, rather than just a tool to be exploited by firms or consumers. A theoretical framework and a series of questions are presented for future research on how online reviews and more generally information flows between actors may impact the efficiency and effectiveness of a marketing system

Helpfulness of Online Review Content: The Moderating Effects of Temporal and Social Cues

This study advances our understanding of consumer evaluation of search product review content, which can vary in its concreteness, by considering contextual review cues that are often tagged to product review content. Anchoring on construal level theory, we differentiate two forms of contextual review cue—namely, temporal cue (i.e., when the review was posted) and social cue (i.e., who posted the review)—and posit their individual and joint moderation effects on the relationship between product review content and perceived review helpfulness. The experimental results reveal interesting insights. First, when the temporal cue indicates near distance, concrete product review content is perceived as more helpful. By contrast, abstract review content is perceived as more helpful when the temporal cue is distant. Second, social cues are non-instrumental in affecting the evaluation of concrete product review content; however, near social cues have bearings on the evaluation of abstract product review content. Third, we also find a significant joint effect of temporal and social cues on the relationship between product review concreteness and review helpfulness. The assessment of abstract reviews’ helpfulness is strengthened when both social and temporal cues reveal near psychological distance. This research contributes not only to the product review literature by providing integrated understanding of product review (i.e., considering both content and contextual cues), but also to construal level theory by identifying the moderating consequences of temporal and social cues as rooted in two dimensions of psychological distance

Normative versus strategic accounts of acknowledgment data: the case of the top-five journals of economics

Two alternative accounts can be given of the information contained in the acknowledgments of academic publications. According to the mainstream normative account, the acknowledgments serve to repay debts towards formal or informal collaborators. According to the strategic account, by contrast, the acknowledgments serve to increase the perceived quality of papers by associating the authors with influential scholars. The two accounts are assessed by analyzing the acknowledgments indexed in Web of Science of 1218 articles published in the "top-five journals" of economics for the years 2015-2019. The analysis is focused on six dimensions: (i) the style of acknowledging texts, (ii) the distribution of mentions, (iii) the identity of the most mentioned acknowledgees, (iv) the shares of highly and lowly mentioned acknowledgees, (v) the hierarchy of the acknowledgment network, and (vi) the correlation at a paper level between intellectual similarity, measured by common references, and social similarity, measured by common acknowledges. Results show that the normative and the strategic account should be considered as valid but partial explanations of acknowledging behavior. Hence, acknowledgments should be used with extreme caution for investigating collaboration practices and they should not be used to produce acknowledgments-based metrics of scholars for evaluative purposes.Comment: 46 pages, 5 figures, 5 table

Multi-layered HITS on Multi-sourced Networks

abstract: Network mining has been attracting a lot of research attention because of the prevalence of networks. As the world is becoming increasingly connected and correlated, networks arising from inter-dependent application domains are often collected from different sources, forming the so-called multi-sourced networks. Examples of such multi-sourced networks include critical infrastructure networks, multi-platform social networks, cross-domain collaboration networks, and many more. Compared with single-sourced network, multi-sourced networks bear more complex structures and therefore could potentially contain more valuable information. This thesis proposes a multi-layered HITS (Hyperlink-Induced Topic Search) algorithm to perform the ranking task on multi-sourced networks. Specifically, each node in the network receives an authority score and a hub score for evaluating the value of the node itself and the value of its outgoing links respectively. Based on a recent multi-layered network model, which allows more flexible dependency structure across different sources (i.e., layers), the proposed algorithm leverages both within-layer smoothness and cross-layer consistency. This essentially allows nodes from different layers to be ranked accordingly. The multi-layered HITS is formulated as a regularized optimization problem with non-negative constraint and solved by an iterative update process. Extensive experimental evaluations demonstrate the effectiveness and explainability of the proposed algorithm.Dissertation/ThesisMasters Thesis Computer Science 201

A usability approach to improving the user experience in web directories

PhDWeb directories are hierarchically organised website collections that offer users subjectbased access to the Web. They played a significant part in navigating the Web in the past but their role has been weakened in recent years due to their cumbersome expanding collections. This thesis presents a unified framework combining the advantages of personalisation and redefined directory search for improving the usability of Web directories. The thesis begins with an examination of classification schemes that identifies the rigidity of hierarchical classifications and their suitability for Web directories in contrast to faceted classifications. This leads on to an Ontological Sketch Modelling (OSM) case study which identifies the misfits affecting user navigation in Web directories from known rigidity issues. The thesis continues with a review of personalisation techniques and a discussion of the user search model of Web directories following the suggested directions of improvement from the case study. A proposed user-centred framework to improve the usability of Web directories which consists of an individual content-based personalisation model and a redefined search model is then implemented as D-Persona and D-Search respectively. The remainder of the thesis is concerned with a usability test of D-Persona and D-Search aimed at discovering the efficiency, effectiveness and user satisfaction of the solution. This involves an experimental design, test results and discussions for the comparative user study. This thesis extracts a formal definition of the rigidity of hierarchies from their characteristics and justifies why hierarchies are still better suited than facets in organising Web directories. Second, it identifies misfits causing poor usability in Web directories based on the discovered rigidity of hierarchies. Third, it proposes a solution to tackle the misfits and improve the usability of Web directories which has been experimentally proved to be successful