Does Position Matter More on Mobile? Ranking Effects across Devices

Achieving a better rank online is often costly. Is the effect of ranking different for mobile devices and traditional PC? This study empirically examines the ranking effect across different device types in an e-commerce environment. With over 4 million observations from Tweaker.net, the largest shopbot in Netherlands, we estimated the ranking effect between mobile and PC. Surprisingly, and contrary to prior findings, our results across different model specifications consistently show that ranking effect is smaller on mobile devices. This study extends the understanding about the effect of position in e-commerce context by empirically examining the ranking effect across devices. This study has important managerial implications for retailers and e-commerce platforms. As the ranking effect is smaller on mobile devices, retailers should take account of the source of traffic (mobile or PC) while bidding for a particular position. And platforms should consider the different ranking effects on different channels

Baidu, Weibo and Renren: The Global Political Economy of Social Media in China

The task of this work is to conduct a global political-economic analysis of China's major social media platforms in the context of transformations of the Chinese economy. It analyses Chinese social media's commodity and capital form. It compares the political economy of Baidu (search engine), Weibo (microblog) and Renren (social networking site) to the political economy of the US platforms Google (search engine), Twitter (microblog) and Facebook (social networking site) in order to analyse differences and commonalities. The comparative analysis focuses on aspects such as profits, the role of advertising, the boards of directors, shareholders, financial market values, terms of use and usage policies. The analysis is framed by the question to which extent China has a capitalist or socialist economy

Report on the Information Retrieval Festival (IRFest2017)

The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017

Microbloggers’ motivations in participatory journalism: A cross-cultural study of America and China

This phenomenological study focuses on the motivations of participatory journalists contributing on microblogs such as Twitter and Weibo. Although online user behavior and motivations have been studied before, few studies have examined motivations of participatory journalists from their own perspective. Moreover, this study is one of the few to explore participatory journalists across different cultures (U.S. and China). The author conducted a total of 13 in-depth interviews with participatory journalists on microblogs from both countries and used a qualitative analysis method to identify the themes and patterns that emerged. Motivations such as earning respect, technology early adoption, self-expression, relationship building, self-enhancement, branding and image building, and financial gain were discussed. De-motivational factors such as time constraints and self-censorship were presented. Motivational differences between the two groups of participants, including what the microblog account represents and the role of participatory journalists, were explained by cultural differences collectivism versus individualism and power distance. Limitations and future research were also discussed

EveTAR: Building a Large-Scale Multi-Task Test Collection over Arabic Tweets

This article introduces a new language-independent approach for creating a large-scale high-quality test collection of tweets that supports multiple information retrieval (IR) tasks without running a shared-task campaign. The adopted approach (demonstrated over Arabic tweets) designs the collection around significant (i.e., popular) events, which enables the development of topics that represent frequent information needs of Twitter users for which rich content exists. That inherently facilitates the support of multiple tasks that generally revolve around events, namely event detection, ad-hoc search, timeline generation, and real-time summarization. The key highlights of the approach include diversifying the judgment pool via interactive search and multiple manually-crafted queries per topic, collecting high-quality annotations via crowd-workers for relevancy and in-house annotators for novelty, filtering out low-agreement topics and inaccessible tweets, and providing multiple subsets of the collection for better availability. Applying our methodology on Arabic tweets resulted in EveTAR , the first freely-available tweet test collection for multiple IR tasks. EveTAR includes a crawl of 355M Arabic tweets and covers 50 significant events for which about 62K tweets were judged with substantial average inter-annotator agreement (Kappa value of 0.71). We demonstrate the usability of EveTAR by evaluating existing algorithms in the respective tasks. Results indicate that the new collection can support reliable ranking of IR systems that is comparable to similar TREC collections, while providing strong baseline results for future studies over Arabic tweets

What am I not seeing? An Interactive Approach to Social Content Discovery in Microblogs

In this paper, we focus on the informational and user experience benefits of user-driven topic exploration in microblog communities, such as Twitter, in an inspectable, controllable and personalized manner. To this end, we introduce ``HopTopics'' -- a novel interactive tool for exploring content that is popular just beyond a user's typical information horizon in a microblog, as defined by the network of individuals that they are connected to. We present results of a user study (N=122) to evaluate HopTopics with varying complexity against a typical microblog feed in both personalized and non-personalized conditions. Results show that the HopTopics system, leveraging content from both the direct and extended network of a user, succeeds in giving users a better sense of control and transparency. Moreover, participants had a poor mental model for the degree of novel content discovered when presented with non-personalized data in the Inspectable interface