Searching for digital images on the web

A systematic literature review on image information needs and behaviors

Purpose

With ready access to search engines and social media platforms, the way people find image information has evolved and diversified in the past two decades. The purpose of this paper is to provide an overview of the literature on image information needs and behaviors.

Design/methodology/approach

Following an eight-step procedure for conducting systematic literature reviews, the paper presents an analysis of peer-reviewed work on image information needs and behaviors, with publications ranging from the years 1997 to 2019.

Findings

Application of the inclusion criteria led to 69 peer-reviewed works. These works were synthesized according to the following categories: research methods, users targeted, image types, identified needs, search behaviors and search obstacles. The reviewed studies show that people seek and use images for multiple reasons, including entertainment, illustration, aesthetic appreciation, knowledge construction, engagement, inspiration and social interactions. The reviewed studies also report that common strategies for image searches include keyword searches with short queries, browsing, specialization and reformulation. Observed trends suggest common deployment of query analysis, survey questionnaires and undergraduate participant pools to research image information needs and behavior.

Originality/value

At this point, after more than two decades of image information needs research, a holistic systematic review of the literature was long overdue. The way users find image information has evolved and diversified due to technological developments in image retrieval. By synthesizing this burgeoning field into specific foci, this systematic literature review provides a foundation for future empirical investigation. With this foundation set, the paper then pinpoints key research gaps to investigate, particularly the influence of user expertise, a need for more diverse population samples, a dearth of qualitative data, new search features and information and visual literacies instruction.

Does Diversity Affect User Satisfaction in Image Search

Diversity has been taken into consideration by existing Web image search engines in ranking search results. However, there is no thorough investigation of how diversity affects user satisfaction in image search. In this article, we address the following questions: (1) How do different factors, such as content and visual presentations, affect users’ perception of diversity? (2) How does search result diversity affect user satisfaction with different search intents? To answer those questions, we conduct a set of laboratory user studies to collect users’ perceived diversity annotations and search satisfaction. We find that the existence of nearly duplicated image results has the largest impact on users’ perceived diversity, followed by the similarity in content and visual presentations. Besides these findings, we also investigate the relationship between diversity and satisfaction in image search. Specifically, we find that users’ preference for diversity varies across different search intents. When users want to collect information or save images for further usage (the Locate search tasks), more diversified result lists lead to higher satisfaction levels. The insights may help commercial image search engines to design better result ranking strategies and evaluation metrics.

An exploration of search session patterns in an image-based digital library

Three months of server transaction logs containing complete clickstream data for an image collection digital library were analysed for usage patterns to better understand user searching and browsing behaviour in this environment. Eleven types of user actions were identified from the log content. The study is novel in its combined analytical techniques and use of clickstream data from an image-based digital library. Three analytical techniques were used to analyse the data: (a) network analysis to better understand the relationship between sequential actions; (b) sequential pattern mining to identify frequent action sequences; and (c) k-means cluster analysis to identify groups of session patterns. The analysis revealed strong ties between several pairs of actions, relatively short pattern sequences that frequently duplicate previous actions and largely uniform session behaviour with little individual item browsing within sessions, indicating users are primarily engaged in purposeful and directed searching. Developers of image-based digital libraries should consider design features that support rapid browsing.

Traitement documentaire de l’image ordinaire : analyse de deux approches d’indexation

Cet article présente les résultats d’une recherche ayant pour objectif de recenser les caractéristiques de deux approches utilisées pour l’indexation d’un ensemble d’images ordinaires représentant des objets de la vie quotidienne. La première approche suppose l’attribution de termes d’indexation extraits d’un dictionnaire visuel, alors que la deuxième approche préconise l’utilisation du vocabulaire libre pour la description des images. L’analyse des termes d’indexation révèle les tendances observées sur le plan terminologique, perceptuel et structurel. Les facteurs ayant influencé l’attribution des termes d’indexation sont également décrits.

Image needs in the context of image use: An exploratory study

As a way of understanding the image needs of users, researchers in the image retrieval field have investigated contextual factors affecting image needs and search behaviours. In terms of both general users’ groups and non-domain-specific collections on the web, the purpose of this study is to investigate how image needs are interwoven with intended uses which are in varying degrees of image use purposes. Thus, the image-seeking questions posted in a social Q&A service were analysed for their content. The findings of this study indicate that image uses as sources of objects are found more frequently than image uses as sources of data. Moreover, in order to analyse a more detailed underlying structure of image needs and uses, image attributes were examined in terms of three categories including semantics (e.g. ofness and aboutness), non-visual features (e.g. bibliographic information) and syntactic features (e.g. focal point). This study indicates that abstract attributes and specific attributes were distinctively recognized depending on image uses, even though proportion generic attributes were found more frequently. Users are likely to seek images using abstract attributes when they intend to use images as sources of object and specific attributes when using the images as sources of data. More importantly, among the contextual attributes, a similarity component was found to be a universal attribute that was used in all seven image uses, while the attributes in the non-visual and syntactic categories were not frequently used. The findings of this study can be applied to image retrieval systems in terms of improving image indexing practices and expanding search interfaces.

Flickr’s potential as an academic image resource: An exploratory study

Many web 2.0 sites are extremely popular and contain vast amounts of content, but how much of this content is useful in academia? This exploratory paper investigates the potential use of the popular web 2.0 image site Flickr as an academic image resource. The study identified images tagged with any one of 12 subject names derived from recognized academic subject categories in the three main Institute for Scientific Information (ISI) citation indexes. Image content analysis was used to determine the types of images found, and term-frequency analysis of associated tags was carried out to provide additional insights into the context behind image placement. The results show that Flickr can be used as a resource for subject-specific images in some subject areas; and that non subject-specific images can also prove to be of value for individual academics.

A new model for semantic photograph description combining basic levels and user-assigned descriptors

Few studies have been conducted to identify users’ desired semantic levels of image access when describing, searching, and retrieving photographs online. The basic level, or the level of abstraction most commonly used to describe an item, is a cognitive theory currently under consideration in image retrieval research. This study investigates potential basic levels of description for online photographs by testing the Hierarchy for Online Photograph Representation (HOPR) model, which is based on a need for a model that addresses users’ basic levels of photograph description and retrieval. We developed the HOPR model using the following three elements as guides: the most popular tags of all time on Flickr, the Pyramid model for visual content description by Jörgensen, Jaimes, Benitez, and Chang, and the nine classes of image content put forth by Burford, Briggs, and Eakins. In an exploratory test of the HOPR model, participants were asked to describe their first reaction to, and possible free-text indexing terms for, a small set of personal photographs. Content analysis of the data indicated a clear set of user preferences that are consistent with prior image description studies. Generally speaking, objects in the photograph and events taking place in the photograph were the most commonly used levels of description. The preliminary HOPR model shows promise for its intended utility, but further refinement is needed through additional research.