Human rights in Google and Bing image search results

[EN] This research analyzes the search results for the term "derechos humanos" in Google Images and Bing Image aiming to inspect the kind of results which are returned and thereby to recognize what type of graphic representations affect the collective imaginary about human rights and which sources or institutions lead this task on the Internet. The methodologies used are the design of a constructed week from the search results, the analysis of the content and an analysis of the Search Engine Optimization (SEO) actions taken by the websites of the identified search results to position themselves in Google.es, since its extrapolation to Bing is considered accepted. This study confirms that symbolic illustrations are prioritized in both search engines and that the websites of the United Nations and the University of Murcia are the ones that are best positioned on the Spanish version of the search engines.Keywords: Human rights; Google Images; Bing Image; Search Engine optimization; SEO.[ES] Esta investigación analiza los resultados de búsqueda para el término ¿derechos humanos¿ en Google Imágenes y Bing Imágenes con el objetivo de ver qué resultados devuelve y conocer así qué tipo de representaciones gráficas ayudan a conformar el imaginario sobre los derechos humanos y qué fuentes o instituciones presentes en Internet lideran este cometido. Las metodologías empleadas son el diseño de una semana construida de los resultados de búsqueda, el análisis del contenido y un análisis de las acciones de Search Engine Optimization (SEO) tomadas por los sitios web de los resultados de búsqueda identificados para posicionarse en Google.es, dado que su extrapolación a Bing se considera aceptada. Este estudio confirma que en ambos buscadores se priorizan las ilustraciones de carácter simbólico y el sitio web de Naciones Unidas y la Universidad de Murcia son las que mejor se posicionan en la versión española de los buscadores.Lopezosa, C.; Martorell, S.; Codina, L. (2022). Los derechos humanos en los resultados de búsqueda de imágenes de Google y Bing. Revista General de Información y Documentación. 32(2):433-451. https://doi.org/10.5209/rgid.8081943345132

Investigating user experience and bias mitigation of the multi-modal retrieval of historical data

Decolonisation has raised the discussion of technology having the responsibility of presenting multiple perspectives to users. This is specifically relevant to African precolonial heritage artefact data, where the data contains the bias of the curators of the artefacts and there are primary concerns surrounding the social responsibility of these systems. Historians have argued that common information retrieval algorithms may further bias results presented to users. While research for mitigating bias in information retrieval is steered in the direction of artificial intelligence and automation, an often-neglected approach is that of user-control. User-control has proven to be beneficial in other research areas and is strongly aligned with the core principles of decolonisation. Thus, the effects on user experience, bias mitigation, and retrieval effectiveness from the addition of user-control and algorithmic variation to a multimodal information retrieval system containing precolonial African heritage data was investigated in this study. This was done by conducting two experiments: 1) an experiment to provide a baseline offline evaluation of various algorithms for text and image retrieval and 2) an experiment to investigate the user experience with a retrieval system that allowed them to compare algorithms. In the first experiment, the differences in retrieval effectiveness between colour-based pre-processing algorithms, shape-based preprocessing algorithms, and pre-processing algorithms based on a combination of colour- and shape-detection, was explored. The differences in retrieval effectiveness between stemming, stopword removal and synonym query expansion was also evaluated for text retrieval. In the second experiment, the manner in which users experience bias in the context of common information retrieval algorithms for both the textual and image data that are available in typical historical archives was explored. Users were presented with the results generated by multiple algorithmic variations, in a variety of different result formats, and using a variety of different search methods, affording them the opportunity to decide what they deem provides them with a more relevant set of results. The results of the study show that algorithmic variation can lead to significantly improved retrieval performance with respect to image-based retrieval. The results also show that users potentially prefer shape-based image algorithms rather than colour-based image algorithms, and, that shape-based image algorithms can lead to significantly improved retrieval of historical data. The results also show that users have justifiable preferences for multimodal query and result formats to improve user experience and that users believe they can control bias using algorithmic variatio

A.: Summarizing social image search results

ABSTRACT Most existing social image search engines present search results as a ranked list of images, which cannot be consumed by users in a natural and intuitive manner. Here, we present a novel algorithm that exploits both visual features and tags of the search results to generate high quality image search result summary. The summary not only breaks the results into visually and semantically coherent clusters, but it also maximizes the coverage of the original search results. We demonstrate the effectiveness of our method against state-of-the-art image summarization and clustering algorithms