Information overload: a concept analysis

Abstract

PurposeWith the shift to an information-based society and to the de-centralisation of information, information overload has attracted a growing interest in the computer and information science research communities. However, there is no clear understanding of the meaning of the term, and while there have been many proposed definitions, there is no consensus. The goal of this work was to define the concept of “information overload”. In order to do so, a concept analysis using Rodgers' approach was performed.Design/methodology/approachA concept analysis using Rodgers' approach based on a corpus of documents published between 2010 and September 2020 was conducted. One surrogate for “information overload”, which is “cognitive overload” was identified. The corpus of documents consisted of 151 documents for information overload and ten for cognitive overload. All documents were from the fields of computer science and information science, and were retrieved from three databases: Association for Computing Machinery (ACM) Digital Library, SCOPUS and Library and Information Science Abstracts (LISA).FindingsThe themes identified from the authors’ concept analysis allowed us to extract the triggers, manifestations and consequences of information overload. They found triggers related to information characteristics, information need, the working environment, the cognitive abilities of individuals and the information environment. In terms of manifestations, they found that information overload manifests itself both emotionally and cognitively. The consequences of information overload were both internal and external. These findings allowed them to provide a definition of information overload.Originality/valueThrough the authors’ concept analysis, they were able to clarify the components of information overload and provide a definition of the concept.

‘It never seems to stop’ Six high school students’ experiences of information overload

“…These factors were related to information content (complexity, fragmentation, depth), information quantity (input duration), information environment (pushed information, unstructured online environment), learning environment (lectures, independent research, long school days) and personal vulnerabilities (life context, personal characteristics). These factors align with previously defined categories of IO triggers (Bawden and Robinson, 2020;Belabbes et al, 2023).…”

“…These factors include the capacity to process information, characteristics of the information itself (complexity, ambiguity, uncertainty, novelty), available time, information quantity, information quality (relevance, validity), task and process parameters, as well as personal factors, all influencing whether a person experiences IO. Belabbes et al (2023) categorise triggers of IO into five main groups: information characteristics, poorly defined information needs, the environment in which the individual interacts with information, the individual's cognitive abilities, and the information environment. Bawden and Robinson (2020, p.12) present four categories of IO triggers: 1) too much information, 2) diversity, complexity, and novelty of information, 3) pervasive and pushed information, and 4) personal factors and individual differences.…”

Managing Information Gaps and Non‐Information

“…While gaps and non-existence of information (or existence of non-information) can clearly be experienced as a deficit, it is not necessarily only detrimental. Increasingly common experience of information overload (Belabbes et al, 2022) has made it apparent that more is not always better. People restrict and control their urge to search, as Haider (2017) puts it, and abstain from information for multiple reasons.…”

Efficient information retrieval model: overcoming challenges in search engines-an overview

“…It targets to improve the accuracy of search results by taking into account the intricate relationships between queries, documents, and users. In essence, IR is becoming more and more individualized as consumers expect search engines to deliver results that are customized to their choices and interests [6].…”