The Effect of News Article Quality on Ad Consumption

Practical news feed platforms generate a hybrid list of news articles and advertising items (e.g., products, services, or information) and many platforms optimize the position of news articles and advertisements independently. However, they should be arranged with careful consideration of each other, as we show in this study, since user behaviors toward advertisements are significantly affected by the news articles. This paper investigates the effect of news articles on users' ad consumption and shows the dependency between news and ad effectiveness. We conducted a service log analysis and showed that sessions with high-quality news article exposure had more ad consumption than those with low-quality news article exposure. Based on this result, we hypothesized that exposure to high-quality articles will lead to a high ad consumption rate. Thus, we conducted million-scale A/B testing to investigate the effect of high-quality articles on ad consumption, in which we prioritized high-quality articles in the ranking for the treatment group. The A/B test showed that the treatment group's ad consumption, such as the number of clicks, conversions, and sales, increased significantly while the number of article clicks decreased. We also found that users who prefer a social or economic topic had more ad consumption by stratified analysis. These insights regarding news articles and advertisements will help optimize news and ad effectiveness in rankings considering their mutual influence.Comment: 30th ACM International Conference on Information and Knowledge Management (CIKM2021

Asking Clarifying Questions:To benefit or to disturb users in Web search?

Modern information-seeking systems are becoming more interactive, mainly through asking Clarifying Questions (CQs) to refine users’ information needs. System-generated CQs may be of different qualities. However, the impact of asking multiple CQs of different qualities in a search session remains underexplored. Given the multi-turn nature of conversational information-seeking sessions, it is critical to understand and measure the impact of CQs of different qualities, when they are posed in various orders. In this paper, we conduct a user study on CQ quality trajectories, i.e., asking CQs of different qualities in chronological order. We aim to investigate to what extent the trajectory of CQs of different qualities affects user search behavior and satisfaction, on both query-level and session-level. Our user study is conducted with 89 participants as search engine users. Participants are asked to complete a set of Web search tasks. We find that the trajectory of CQs does affect the way users interact with Search Engine Result Pages (SERPs), e.g., a preceding high-quality CQ prompts the depth users to interact with SERPs, while a preceding low-quality CQ prevents such interaction. Our study also demonstrates that asking follow-up high-quality CQs improves the low search performance and user satisfaction caused by earlier low-quality CQs. In addition, only showing high-quality CQs while hiding other CQs receives better gains with less effort. That is, always showing all CQs may be risky and low-quality CQs do disturb users. Based on observations from our user study, we further propose a transformer-based model to predict which CQs to ask, to avoid disturbing users. In short, our study provides insights into the effects of trajectory of asking CQs, and our results will be helpful in designing more effective and enjoyable search clarification systems.This study is supported under the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as cash and in-kind contribution from Singapore Telecommunications Limited (Singtel), through Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU). This study is also supported by the NWO Smart Culture - Big Data/Digital Humanities (314-99-301), the NWO Innovational Research Incentives Scheme Vidi (016.Vidi.189.039), and the H2020- EU.3.4. - SOCIETAL CHALLENGES - Smart, Green, And Integrated Transport (814961)

Search engine ranking factors analysis : Moz digital marketing company survey study

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThe use of the Internet increases every year in the world for multiple purposes and at significant rates. In the same way, access to electronic business and personal pages allowing commercial transactions follows these high evolution rates. Many studies on this subject have pointed that it is important for most businesses to have a web presence. The key to be found by the right product or service target audience, at the right moment, according to most of authors, lies with search engines (SE) advent. However, there had been frequently changes in search engines ranking website classification algorithms during the last years. To accomplish this model evolution, the Search Engine Optimization (SEO) professionals must to frequently adopt to constant changes regarding ranking classification strategies from SE schemas of work. In this work the author explored a wide range of factors that may influence search engine result pages (SERP’s) and examined recent aspects of user experience over a website that are increasing importance regarding the optimization to be done over the web pages, internal and external page links, and its technical components. In addition, it seems that the user action and involvement over the website are key factors that Google will probably continue to adopt to determine websites rank in SERP’s. As an empirical study, all efforts to discover the SE website promotion ranking factors are based on trial and error activities and there is no official knowledge base regarding these protected secrets kept by the major players of this valuable market. Due to the lack of published academic research works in this area, the present work has discovered and documented SE ranking factors based on survey data by a large quantity of companies in digital marketing segment. At the end of the project the author intends to present the state-of-the-art in this field of study as well as some market perception evolution of this subject based heavily on practical experiments and most recent literature in this area. Moreover, it is growing the debate about the limits of digital marketing. Due the powerful influence of SE to market and people behavior, the presented study data and considerations raise an important forum of discussion now and in the future concerning ethics and socially acceptable limits and controls over personal information on the internet

Using contextual information to understand searching and browsing behavior

There is great imbalance in the richness of information on the web and the succinctness and poverty of search requests of web users, making their queries only a partial description of the underlying complex information needs. Finding ways to better leverage contextual information and make search context-aware holds the promise to dramatically improve the search experience of users. We conducted a series of studies to discover, model and utilize contextual information in order to understand and improve users' searching and browsing behavior on the web. Our results capture important aspects of context under the realistic conditions of different online search services, aiming to ensure that our scientific insights and solutions transfer to the operational settings of real world applications