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About

Carla Teixeira Lopes is an assistant Professor in the Department of Informatics Engineering, University of Porto, Portugal. She is also a researcher at INESC TEC since 2014. She received a PhD in Informatics Engineering from the University of Porto in 2013. Her research interests lie at the intersection of information retrieval and human-computer interaction. She is interested in studying information search behaviour and in developing tools that help people search more successfully. Lately, she has been focused in exploring how context can help improve the experience of health consumers searching the Web.

Interest
Topics
Details

Details

003
Publications

2019

A classification scheme for analyses of messages exchanged in online health forums

Authors
Lopes, CT; Da Silva, BG;

Publication
INFORMATION RESEARCH-AN INTERNATIONAL ELECTRONIC JOURNAL

Abstract
Introduction. Online health forums help to surface and organize patients' knowledge and make it useful for many. They are used by many to seek for advice or to share what they know about health subjects. Being an important communication medium, it's important to understand why and how it is used. Method. In this work we examine and categorize messages of an online health forum, with the purpose of providing a classification scheme that can be used by the research community in future analyses. The definition of the classification scheme was iterative and its inter-rater reliability was assessed twice using Cohen's Kappa statistic. Analysis. The classification scheme arose from a content analysis of 3,399 messages from several communities of an online health forum. Findings. The scheme is divided into four sections of categories and each section has several subcategories, in total there are 23 subcategories. The inter-rater agreement assessment of the scheme showed a good consistency between coders. The majority of the categories has a Cohen's Kappa agreement above 0.4. Conclusion. The proposed classification scheme facilitates the analysis of messages exchanged in online health forums for several purposes, including studies of information seeking.

2019

Interplay of Documents' Readability, Comprehension and Consumer Health Search Performance Across Query Terminology

Authors
Lopes, CT; Ribeiro, C;

Publication
Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, CHIIR 2019, Glasgow, Scotland, UK, March 10-14, 2019

Abstract
Because of terminology mismatches, health consumers frequently face difficulties while searching the Web for health information. Difficulties arise in query formulation but also in understanding the retrieved documents. In this work we analyze how documents' readability affects users' comprehension and how both affect the retrieval performance, measured in different ways. In addition, we analyze how performance measures relate with each other. For this purpose we have conducted a laboratory user study with 40 participants. We found that readability is essential for a document to be at least partially relevant and that it becomes even more important if the document has medico-scientific terminology. Moreover, the relevance of a document to a specific user highly depends on its comprehension. In lay queries we found the medical accuracy of users' answers is related to the session's relevance assessments. This shows that users can, at least in part, relate their relevance assessments with the medical accuracy of the documents. On the other hand, this relationship does not exist with medico-scientific queries. © 2019 Copyright held by the owner/author(s). Publication rights licensed to Association for Computing Machinery.

2019

Assisting Health Consumers While Searching the Web through Medical Annotations

Authors
Lopes, CT; Sousa, H;

Publication
Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, CHIIR 2019, Glasgow, Scotland, UK, March 10-14, 2019

Abstract

2019

Characterizing and comparing Portuguese and English Wikipedia medicine-related articles

Authors
Domingues, G; Lopes, CT;

Publication
COMPANION OF THE WORLD WIDE WEB CONFERENCE (WWW 2019 )

Abstract
Wikipedia is the largest on-line collaborative encyclopedia, containing information from a plethora of fields, including medicine. It has been shown that Wikipedia is one of the top visited sites by readers looking for information on this topic. The large reliance on Wikipedia for this type of information drives research towards the analysis of the quality of its articles. In this work, we evaluate and compare the quality of medicine-related articles in the English and Portuguese Wikipedia. For that we use metrics such as authority, completeness, complexity, informativeness, consistency, currency and volatility, and domain-specific measurements, in order to evaluate and compare the quality of medicine related articles in the English and Portuguese Wikipedia. We were able to conclude that the English articles score better across most metrics than the Portuguese articles.

2019

Graph-of-entity: A model for combined data representation and retrieval

Authors
Devezas, JL; Lopes, CT; Nunes, S;

Publication
OpenAccess Series in Informatics

Abstract
Managing large volumes of digital documents along with the information they contain, or are associated with, can be challenging. As systems become more intelligent, it increasingly makes sense to power retrieval through all available data, where every lead makes it easier to reach relevant documents or entities. Modern search is heavily powered by structured knowledge, but users still query using keywords or, at the very best, telegraphic natural language. As search becomes increasingly dependent on the integration of text and knowledge, novel approaches for a unified representation of combined data present the opportunity to unlock new ranking strategies. We tackle entity-oriented search using graph-based approaches for representation and retrieval. In particular, we propose the graph-of-entity, a novel approach for indexing combined data, where terms, entities and their relations are jointly represented. We compare the graph-of-entity with the graph-of-word, a text-only model, verifying that, overall, it does not yet achieve a better performance, despite obtaining a higher precision. Our assessment was based on a small subset of the INEX 2009 Wikipedia Collection, created from a sample of 10 topics and respectively judged documents. The offline evaluation we do here is complementary to its counterpart from TREC 2017 OpenSearch track, where, during our participation, we had assessed graph-of-entity in an online setting, through team-draft interleaving. © José Devezas, Carla Lopes, and Sérgio Nunes.

Supervised
thesis

2019

ArchGraph: Desenho e concepção de um protótipo vertical de infraestrutura para arquivos semânticos

Author
Nuno Miguel Cardoso Lopes de Freitas

Institution
UP-FEUP

2019

HealthSuggestions: moving beyond the beta version

Author
Paulo Miguel Pereira dos Santos

Institution
UP-FEUP

2019

Social Media and Chatbots use for Chronic Disease Patients Support: Case Study from an Online Community Regarding Therapeutic use of Cannabis

Author
Alice Rangel Teixeira

Institution
UP-FEUP

2019

Ferramentas para o Planeamento e Avaliação de Risco de Dados de Investigação: o caso do i3S no âmbito do RGPD

Author
Maria do Rosário Ferreira Nunes

Institution
UP-FEUP

2019

Automatic Prediction of Health Literacy through an eye tracker

Author
Edgar Duarte Ramos

Institution
UP-FEUP