Analysis of web information-seeking behavior of users with different levels of health literacy

Literacia em Saúde é definida como "o nível pelo qual os indivíduos podem obter, processar, compreender e comunicar informação relacionada com saúde necessária para tomar decisões de saúde informadas". Os utilizadores com um baixo nível de literacia em saúde têm menos conhecimentos das suas condições médicas, maior dificuldade em seguir as instruções e compreender a informação dada pelos médicos. Cada vez mais, as pessoas recorrem à web para pesquisar sobre informação de saúde. As dificuldades que os utilizadores de baixa literacia têm no mundo real provavelmente persistem no mundo virtual. O principal objetivo deste estudo é analisar os comportamentos de pesquisa de utilizadores com diferentes níveis de literacia em saúde. Pretende-se identificar diferenças entre pessoas com baixa e alta literacia de saúde que depois possam ser utilizadas para a melhoria dos sistemas de recuperação e contribuir, entre outros, para facilitar o acesso à informação e educação das pessoas com baixa literacia. Este estudo surge na sequência de um trabalho prévio que incluiu a anotação dos registos de vídeo de uma experiência com utilizadores realizada anteriormente. Com base na versão preliminar de análise do trabalho anterior, foi proposto um esquema de classificação de eventos que engloba tipos de interação relativos ao navegador, motor de pesquisa e páginas web. Cada tipo de interação é composto por eventos que, por sua vez estão associados a variáveis de análise. Dentro deste esquema, foram construídos módulos para analisar as interrogações de pesquisa submetidas. Com base neste esquema, foi revista a anotação dos vídeos e foi realizada a análise de dados de forma descritiva e inferencial. Os principais resultados demonstram que o grupo de baixa literacia em saúde utilizou sobretudo a caixa do motor de pesquisa e a funcionalidade de voltar atrás; interagiu mais tempo com página de resultados do motor de pesquisa, clicando mais com o botão esquerdo do rato e fazendo scrolling. Por outro lado, o grupo de alta literacia em saúde utilizou mais a barra de endereço e a funcionalidade de selecionar o texto do URL. Na página de resultados do motor de pesquisa este grupo fez mais cliques com o botão direito. A nível de reformulação de interrogações, que ocorrem no contexto da mesma necessidade de informação, os utilizadores com baixa literacia em saúde usaram mais as reformulações "totalmente novas", ou seja, sem termos em comum com a interrogação anterior. Por sua vez, o grupo de alta literacia em saúde fez mais reformulações.Health Literacy is "the level by which individuals can obtain, process, understand and communicate health-related information necessary to make informed health decisions". Users with a low level of health literacy are less aware of their medical conditions, more difficult to follow instructions and understand doctors' information. Increasingly, people turn to the web to search for health information. Low literacy users' difficulties in the real world are likely to continue to exist in the virtual world. The main objective of this study is to analyze the search behavior of users with different levels of health literacy. It intends to identify differences between people with low and high health literacy that can then be used to improve retrieval systems and contribute, among others, to facilitate access to information and education by people with low literacy. This study follows a previous work that included annotating video records of experience with users previously carried out. Based on the preliminary analysis version of the previous work, an event classification scheme was proposed that includes types of interactions related to the browser, search engine, and web pages. Each type of interaction is composed of events that, in turn, are associated with analysis variables. Within this scheme, modules were built to analyze the formulation of search queries. Based on this scheme, the annotation of the videos was revised, and the data analysis was performed in a descriptive and inferential manner. The main results demonstrate that the low health literacy group used mainly the search engine box and the backward feature. On the search engine results page, they clicked more with the left mouse button. On the results page, they spent more time on the interaction, mainly scrolling. On the other hand, the high health literacy group made more use of the address bar and the functionality of selecting the URL text. On the search engine results page, this group made more right-clicks. At the level of reformulations, which occur in the context of the same need for information, users with low health literacy used more "totally new" reformulations, that is, without terms in common with the previous question. In turn, the high health literacy group did more reformulations

Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)

Opinion mining and sentiment analysis has become ubiquitous in our society, with applications in online searching, computer vision, image understanding, artificial intelligence and marketing communications (MarCom). Within this context, opinion mining and sentiment analysis in marketing communications (OMSAMC) has a strong role in the development of the field by allowing us to understand whether people are satisfied or dissatisfied with our service or product in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To the best of our knowledge, there is no science mapping analysis covering the research about opinion mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work during the last two decades in this interdisciplinary area and to show trends that could be the basis for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer and InCites based on results from Web of Science (WoS). The results of this analysis show the evolution of the field, by highlighting the most notable authors, institutions, keywords, publications, countries, categories and journals.The research was funded by Programa Operativo FEDER Andalucía 2014‐2020, grant number “La reputación de las organizaciones en una sociedad digital. Elaboración de una Plataforma Inteligente para la Localización, Identificación y Clasificación de Influenciadores en los Medios Sociales Digitales (UMA18‐ FEDERJA‐148)” and The APC was funded by the same research gran

4th. International Conference on Advanced Research Methods and Analytics (CARMA 2022)

Research methods in economics and social sciences are evolving with the increasing availability of Internet and Big Data sources of information. As these sources, methods, and applications become more interdisciplinary, the 4th International Conference on Advanced Research Methods and Analytics (CARMA) is a forum for researchers and practitioners to exchange ideas and advances on how emerging research methods and sources are applied to different fields of social sciences as well as to discuss current and future challenges. Due to the covid pandemic, CARMA 2022 is planned as a virtual and face-to-face conference, simultaneouslyDoménech I De Soria, J.; Vicente Cuervo, MR. (2022). 4th. International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. https://doi.org/10.4995/CARMA2022.2022.1595

Formulating Complex Queries Using Templates

While many users have relatively general information needs, users who are familiar with a certain topic may have more specific or complex information needs. Such users already have some knowledge of a subject and its concepts, and they need to find information on a specific aspect of a certain entity, such as its cause, effect, and relationships between entities. To successfully resolve this kind of complex information needs, in our study, we investigated the effectiveness of topic-independent query templates as a tool for assisting users in articulating their information needs. A set of query templates, which were written in the form of fill-in-the-blanks was designed to represent general semantic relationships between concepts, such as cause-effect and problem-solution. To conduct the research, we designed a control interface with a single query textbox and an experimental interface with the query templates. A user study was performed with 30 users. Okapi information retrieval system was used to retrieve documents in response to the users’ queries. The analysis in this paper indicates that while users found the template-based query formulation less easy to use, the queries written using templates performed better than the queries written using the control interface with one query textbox. Our analysis of a group of users and some specific topics demonstrates that the experimental interface tended to help users create more detailed search queries and the users were able to think about different aspects of their complex information needs and fill in many templates. In the future, an interesting research direction would be to tune the templates, adapting them to users’ specific query requests and avoiding showing non-relevant templates to users by automatically selecting related templates from a larger set of templates

Beyond Personalization: Research Directions in Multistakeholder Recommendation

Recommender systems are personalized information access applications; they are ubiquitous in today's online environment, and effective at finding items that meet user needs and tastes. As the reach of recommender systems has extended, it has become apparent that the single-minded focus on the user common to academic research has obscured other important aspects of recommendation outcomes. Properties such as fairness, balance, profitability, and reciprocity are not captured by typical metrics for recommender system evaluation. The concept of multistakeholder recommendation has emerged as a unifying framework for describing and understanding recommendation settings where the end user is not the sole focus. This article describes the origins of multistakeholder recommendation, and the landscape of system designs. It provides illustrative examples of current research, as well as outlining open questions and research directions for the field.Comment: 64 page

Investigating User Search Tactic Patterns and System Support in Using Digital Libraries

This study aims to investigate users\u27 search tactic application and system support in using digital libraries. A user study was conducted with sixty digital library users. The study was designed to answer three research questions: 1) How do users engage in a search process by applying different types of search tactics while conducting different search tasks?; 2) How does the system support users to apply different types of search tactics?; 3) How do users\u27 search tactic application and system support for different types of search tactics affect search outputs? Sixty student subjects were recruited from different disciplines in a state research university. Multiple methods were employed to collect data, including questionnaires, transaction logs and think-aloud protocols. Subjects were asked to conduct three different types of search tasks, namely, known-item search, specific information search and exploratory search, using Library of Congress Digital Libraries. To explore users\u27 search tactic patterns (RQ1), quantitative analysis was conducted, including descriptive statistics, kernel regression, transition analysis, and clustering analysis. Types of system support were explored by analyzing system features for search tactic application. In addition, users\u27 perceived system support, difficulty, and satisfaction with search tactic application were measured using post-search questionnaires (RQ2). Finally, the study examined the causal relationships between search process and search outputs (RQ 3) based on multiple regression and structural equation modeling. This study uncovers unique behavior of users\u27 search tactic application and corresponding system support in the context of digital libraries. First, search tactic selections, changes, and transitions were explored in different task situations - known-item search, specific information search, and exploratory search. Search tactic application patterns differed by task type. In known-item search tasks, users preferred to apply search query creation and following search result evaluation tactics, but less query reformulation or iterative tactic loops were observed. In specific information search tasks, iterative search result evaluation strategies were dominantly used. In exploratory tasks, browsing tactics were frequently selected as well as search result evaluation tactics. Second, this study identified different types of system support for search tactic application. System support, difficulty, and satisfaction were measure in terms of search tactic application focusing on search process. Users perceived relatively high system support for accessing and browsing tactics while less support for query reformulation and item evaluation tactics. Third, the effects of search tactic selections and system support on search outputs were examined based on multiple regression. In known-item searches, frequencies of query creation and accessing forwarding tactics would positively affect search efficiency. In specific information searches, time spent on applying search result evaluation tactics would have a positive impact on success rate. In exploratory searches, browsing tactics turned out to be positively associated with aspectual recall and satisfaction with search results. Based on the findings, the author discussed unique patterns of users\u27 search tactic application as well as system design implications in digital library environments

The Use of Social Tags in Text and Image Searching on the Web.

In recent years, tags have become a standard feature on a diverse range of sites on the Web, accompanying blog posts, photos, videos, and online news stories. Tags are descriptive terms attached to Internet resources. Despite the rapid adoption of tagging, how people use tags during the search process is not well understood. There is little empirical data on the use and perceptions of tags created by those other than the searcher. Previous research on tags focused on the motivations and behaviors of taggers, although non-taggers represent a larger proportion of Web users than taggers. This study examines how people use tags, created by others, during the search process. Forty-eight subjects were each assigned four search tasks in a within-subjects study. Subjects searched for text documents and images in a controlled laboratory setting, using information retrieval interfaces differing in their incorporation of tags. User behavior and perception data were collected through search logs and interviews. Both direct and indirect uses of tags across the search process were examined. Tags are used directly when they are clicked on, resulting in a new query, while tags are used indirectly when used for judgments of relevance or to obtain additional terms for query reformulation. Tags increased interactions with the information retrieval system, as subjects issued more queries and saw more search results when using the tagged interface. For both text and image searches, tags were used for query reformulation, predictive judgment, and evaluative judgment of relevance. Subjects interacted most frequently with tags on the search results page, using them for query reformulation and predictive judgment. Tags were more likely to be used for predictive judgment in text searches than in image searches. Subjects’ understanding of tags focused on the role of tags in search, especially findability through a search engine. Tags were not uniformly perceived as being user-generated; site owners and automatic generation were mentioned as sources of tags. Several implications for the design of search interfaces and presentation of tags to support information interactions are discussed in the conclusion.Ph.D.InformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/89816/1/kimym_1.pd