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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

Publications

2017

Effects of Language and Terminology of Query Suggestions on Medical Accuracy Considering Different User Characteristics

Authors
Lopes, CT; Paiva, D; Ribeiro, C;

Publication
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY

Abstract
Searching for health information is one of the most popular activities on the web. In this domain, users often misspell or lack knowledge of the proper medical terms to use in queries. To overcome these difficulties and attempt to retrieve higher-quality content, we developed a query suggestion system that provides alternative queries combining the Portuguese or English language with lay or medico-scientific terminology. Here we evaluate this system's impact on the medical accuracy of the knowledge acquired during the search. Evaluation shows that simply providing these suggestions contributes to reduce the quantity of incorrect content. This indicates that even when suggestions are not clicked, they are useful either for subsequent queries' formulation or for interpreting search results. Clicking on suggestions, regardless of type, leads to answers with more correct content. An analysis by type of suggestion and user characteristics showed that the benefits of certain languages and terminologies are more perceptible in users with certain levels of English proficiency and health literacy. This suggests a personalization of this suggestion system toward these characteristics. Overall, the effect of language is more preponderant than the effect of terminology. Clicks on English suggestions are clearly preferable to clicks on Portuguese ones.

2017

Predicting the situational relevance of health web documents

Authors
Oroszlanyova, M; Lopes, CT; Nunes, S; Ribeiro, C;

Publication
2017 12th Iberian Conference on Information Systems and Technologies (CISTI)

Abstract

2017

Towards understanding consumers' quality evaluation of online health information: A case study

Authors
Ye, Z; Gwizdka, J; Lopes, CT; Zhang, Y;

Publication
Proceedings of the Association for Information Science and Technology

Abstract

2016

Can we detect English proficiency through reading behavior? A preliminary study

Authors
Silva, IG; Lopes, CT; Ellison, M;

Publication
2016 11TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI)

Abstract
If it were possible to automatically detect proficiency in languages using data from eye movements, new levels of customizing computer applications could possibly be achieved. An example in case is web searches where suggestions and results could be adjusted to the user's knowledge of the language. The objective of this study is to compare the reading habits of users with high and low English language proficiency, having in mind the possible automatic detection of the English proficiency level through reading. For this purpose, a study was conducted with two types of user, those with a high level of proficiency (Proficient Users), and those with low proficiency (Basic Users) in the English language. An eye-tracker was used to collect users' eye movements while reading a text in English. Results show that users with high proficiency engage in more careful reading. In contrast, low English proficiency users take more time to read, revisit sentences and paragraphs more often, have more and longer fixations and also a higher number of saccades. As expected, these users have more difficulties in understanding the text.

2016

Effects of Language and Terminology on the Usage of Health Query Suggestions

Authors
Lopes, CT; Ribeiro, C;

Publication
EXPERIMENTAL IR MEETS MULTILINGUALITY, MULTIMODALITY, AND INTERACTION, CLEF 2016

Abstract
Searching for health information is one of the most popular activities on the Web. In this domain, users frequently encounter difficulties in query formulation, either because they lack knowledge of the proper medical terms or because they misspell them. To overcome these difficulties and attempt to retrieve higher-quality content, we developed a query suggestion system that provides alternative queries combining the users' native language and English language with lay and medico-scientific terminology. To assess how the language and terminology impact the use of suggestions, we conducted a user study with 40 subjects considering their English proficiency, health literacy and topic familiarity. Results show that suggestions are used most often at the beginning of search sessions. English suggestions tend to be preferred to the ones formulated in the users' native language, at all levels of English proficiency. Medico-scientific suggestions tend to be preferred to lay suggestions at higher levels of health literacy.

Supervised
thesis

2016

HealthTranslator: automatic annotation of Web documents in order to assist health consumer’s searches

Author
Hugo Miguel Ribeiro de Sousa

Institution
UP-FEUP

2016

Query expansion strategies for laypeople-centred health information retrieval

Author
Ricardo Daniel Soares da Silva

Institution
UP-FEUP

2016

Análise de conteúdo em fóruns de saúde na Web: proposta de um esquema de classificação

Author
Bárbara Lia Guimarães da Silva

Institution
UP-FEUP