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In this paper I analytically review the literature on the information overload problem, with special reference to the business organizations and entrepreneurship and the study mainly reveals that the problem of the information overload has been existed for many years, whereas in current years the problem has become more clearly recognized and experienced. A concern stressed in the literature is the paradoxical situation that most probably there is an abundance of information available and it is often difficult to obtain useful, and relevant information when it may be needed. Both perceptions and the actual effects of information overload have exacerbated by rapid advances made in the information and communication technology, whereas it is not clear cut as to whether Internet has worsened/improved the situation. Some solutions have put forward to reduce the information overload are a reduction in duplication of the information found in professional literature; the adoption of the personal information management strategies, along with the integration of software solutions such as push technology and intelligent agents; and the provision of value-added information. Main emphasis is placed on the technology as a tool and not driver, while increased in information literacy may provide key to reducing the information overload in organisations.

Based on a national survey of 1111 Chinese citizens, this study analyzes how exposure to fake news and perceptions of information overload are associated with the third-person effect. The findings indicate that fake news exposure correlates with perceived information overload and third-person perceptions of fake news. Respondents with higher levels of perceived information overload also report stronger third-person perceptions. In addition, Chinese respondents who believe that fake news affects others more than themselves are less likely to support stricter controls of fake news.

The proliferation of information technologies has changed how Internet users around the world seek information. While information and communication technologies have transformed the structure of the Chinese economy, they have also brought challenges to the informational realms of everyday lives. However, there is a lack of empirical research exploring if users have encountered barriers in seeking online information for daily tasks. This mixed-methods study focuses on the disruptive influence of digital technologies on everyday information seeking practices, namely, the paradoxical co-existence of information overload and the lack of information sources. Results suggest that Chinese Internet users face a dilemma of receiving redundant online information and yet still experience a lack of high-quality information sources online. Findings from this research provide new perspectives of understanding the role of digital technologies in everyday life and also extend the dimensions of digital divides from internet access to disparities in information practices and experiences.

This paper analyzes notions and models of optimized cognition emerging at the intersections of psychology, neuroscience, and computing. What I somewhat polemically call the algorithms of mindfulness describes an ideal that determines algorithmic techniques of the self, geared at emotional resilience and creative cognition. A reframing of rest, exemplified in corporate mindfulness programs and the design of experimental artificial neural networks sits at the heart of this process. Mindfulness trainings provide cues as to this reframing, for they detail each in their own way how intermittent periods of rest are to be recruited to augment our cognitive capacities and combat the effects of stress and information overload. They typically rely on and co-opt neuroscience knowledge about what the brains of North Americans and Europeans do when we rest. Current designs for artificial neural networks draw on the same neuroscience research and incorporate coarse principles of cognition in brains to make machine learning systems more resilient and creative. These algorithmic techniques are primarily conceived to prevent psychopathologies where stress is considered the driving force of success. Against this backdrop, I ask how machine learning systems could be employed to unsettle the concept of pathological cognition itself.

Attraction recommendation plays an important role in tourism, such as solving information overload problems and recommending proper attractions to users. Currently, most recommendation methods are dedicated to improving the accuracy of recommendations. However, recommendation methods only focusing on accuracy tend to recommend popular items that are often purchased by users, which results in a lack of diversity and low visibility of non-popular items. Hence, many studies have suggested the importance of recommendation diversity and proposed improved methods, but there is room for improvement. First, the definition of diversity for different items requires consideration for domain characteristics. Second, the existing algorithms for improving diversity sacrifice the accuracy of recommendations. Therefore, the article utilises the topic ‘features of attractions’ to define the calculation method of recommendation diversity. We developed a two-stage optimisation model to enhance recommendation diversity while maintaining the accuracy of recommendations. In the first stage, an optimisation model considering topic diversity is proposed to increase recommendation diversity and generate candidate attractions. In the second stage, we propose a minimisation misclassification cost optimisation model to balance recommendation diversity and accuracy. To assess the performance of the proposed method, experiments are conducted with real-world travel data. The results indicate that the proposed two-stage optimisation model can significantly improve the diversity and accuracy of recommendations.

Written language is the primary means by which scientific research findings are disseminated. Yet in the era of information overload, dissemination of a field of research may require additional efforts given the sheer volume of material available on any specific topic. Topic models are unsupervised natural language processing methods that analyze nonnumeric data (i.e., text data) in abundance. These tools aggregate, and make sense of, those data making them interpretable to interested audiences. In this perspective piece, we briefly describe topic models, including their purpose, function, and applicability for health education researchers and practitioners. We note how topic models can be applied in several contexts, including social media–based analyses, and mapping trends in scientific literature over time. As a tool for studying words, and patterns of words, topic models stand to improve our understanding of events prior and those occurring in the moment and help us look ahead into the future.

Information overload has always been a challenge for businesspeople as well as professionals from other types of organizations. And today with search algorithms and artificial intelligence (AI) such an ever-present part of daily life and media consumption, the challenges in learning how to filter information for oneself for effective processing, interpretation and analysis have only increased. This article presents several frameworks that were created for instructing students to assist with addressing this. They were tested and refined over four years in a core MBA course focused on decision making and project-based work. They include ways to conceptualize the broad areas of information available for business decision making as well as how to identify information by thinking about who is producing it, why they are producing it and who their key customers are. Other frameworks presented deal with ways to identify pertinent information and how to process and work with it as part of a research investigation. These frameworks are presented as tools that can be used by business school instructors, but certainly have a broader application as useful guidelines for anyone hoping to be a better collector and processor of relevant information for decision making and project work.

Caregivers may receive information at a rate far higher than their individual abilities to process. Hence, caregivers can cause less desirable health outcomes for their care recipients. This study sought to identify caregiver information overload in comparison to noncaregivers. Relating factors such as caregiving contexts, health status, and personal health literacy were also compared between caregivers and noncaregivers. Using a nationally representative survey, the Health Information National Trends Survey, the differences between caregivers and noncaregivers regarding information overload were compared. A total of 2,918 noncaregivers and 484 caregivers were identified. More than two-thirds of the study sample demonstrated information overload regardless of caregiving status. Male, less educated, lower income, married, and employed caregivers are likely overloaded with information. Caregivers with information overload show less healthy conditions and expressed more information seeking burden. Effective countermeasures of heavy information overload should be devised based on specific causes and their accompanying consequences.

The commentary addresses the government’s role in mitigating information asymmetry problems during pandemic crisis response. We use the outbreak of COVID-19 in Wuhan, China, as a case to show the use of social media as a key mechanism in shaping the actions of the central government in its coordination with the local governments during the pandemic response. The Chinese government effectively collaborated with a social media platform to not only create a dedicated channel to allow citizens to post information about the pandemic to accelerate the speed of relief but also mobilize citizens and nonprofit organizations to support government response and recovery efforts. This suggests that social media can provide a venue for the government to not only tackle the information overload but also mitigate the friction among levels of governments.

Work motivation is a core component of many management courses. However, its effective teaching can be hampered by the fragmentation and seeming incoherence of the various theories of work motivation. To address this challenge, we describe an interactive role-play activity that induces students to synthesize, apply, and compare several theories of motivation. In the first part of the exercise, students work in small groups to prepare a role-play skit illustrating a specific theory of motivation. In the second part, groups present their role-play skits in front of the class, and the rest of the students try to determine which theories were performed. Next, the debriefing session encourages students to discuss, compare, and contrast the theories. Though the present exercise focuses on four theories—the hierarchy of needs, the two-factor theory, expectancy theory, and self-determination theory—the activity can be easily adapted to incorporate other models of motivation.

Undoubtedly, the entrepreneur is the key to the initiation of the entrepreneurial process and firm performance. Since entrepreneurs vary in their background and abilities, researchers have examined the factors impacting their performance. Previous results show that personality characteristics and self-efficacy of entrepreneurs had a positive impact on their performance. In this study, we consider that entrepreneurs’ self-efficacy (ESE) is a multi-dimensional concept and identify six inherent dimensions. Further, we include two other variables that have not received adequate attention in the literature so far, namely, entrepreneurial information overload (EIO) and entrepreneurs’ human resources management (HRM) behaviour. To undertake empirical analysis, we developed a conceptual framework that proposes a negative impact of entrepreneurial information overload on entrepreneurial self-efficacy and entrepreneurs’ HRM behaviour. Responses from 403 entrepreneurs of a large emerging economy were subjected to path-based multiple regression analysis. The results reveal that information overload has a direct impact on all the ESE dimensions, except on planning tasks. Although there is no direct effect of EIO on entrepreneurs’ HRM behaviour, there is an indirect effect through the mediating role of ESE. These results suggest the need for appropriate strategies to help entrepreneurs to deal with information overload and ways to improve specific dimensions of ESE as necessary. Further, this study provides a platform for empirical research for future studies.

In response to coronavirus disease (COVID-19) in 2020, the national Salud America! Latino health equity program at University of Texas Health San Antonio applied its digital content curation model to create and communicate culturally relevant news, stories, and data to raise immediate awareness and generate action against the pandemic’s inequitable impacts on U.S. Latinos. Digital content curation is an emerging public health communication strategy using a systematic, refined process to create tailored online and social health messages and prevent mixed messaging and information overload for an audience. Salud America! curated culturally relevant digital content to raise awareness of the pandemic’s inequitable impact on Latinos and promote solutions for health equity, with a unique combination of website blog posts exploring pandemic effects on Latinos, peer-modeled stories of people responding meaningfully to the crisis, podcast episodes and Tweetchats engaging people in COVID-19 solutions for Latinos, action tools and campaigns equipping school leaders to make grassroots changes, and supplying advocates with a local data tool on health equity identification. The digital health promotion intervention produced curated content that spiked program website traffic to record highs, revealing the model’s effectiveness in increasing exposure to culturally relevant and action-oriented information for a novel topic.

Information avoidance is a behavior that could either prevent or delay consumption of information. While information avoidance has been documented in various fields of interest, its overall dynamics in the context of library and information science remains a research blankspot. The overall intent of this paper is to develop a model that examines the moderating effect of information overload and academic procrastination on the information avoidance behavior among Filipino undergraduate thesis writers. Capitalizing on Structural Equation Modeling (SEM) design, a total of 215 Filipino undergraduate thesis writers participated in the study. A multi-aspect questionnaire was used to measure the following variables: information overload, academic procrastination and information avoidance. Descriptive and inferential statistics were used to analyze the data. Results show that when students have a positive attitude towards reading, the more likely they are to employ better reading strategies and the less likely they are to exhibit information avoidance. On the other hand, the more reading strategies are used, the lower is information avoidance. Additionally, the tendency to procrastinate has less effect on the relationship between reading strategies and information avoidance and the tendency to procrastinate and acquire excessive information has less effect on the relationship between reading attitudes and information avoidance. Implications for university settings are also discussed in this paper.

Considerable research has focused on the positive effects of information technology use. However, emerging research and practice commentary highlight the importance of considering the negative side of information technology use. The current study investigates how enterprise social media use (i.e. work- and social-related use) influences employees’ perceived overload (i.e. information and social overload), which in turn affects enterprise social media-related strain. In addition, we posit that communication visibility moderates the nonlinear relationship between enterprise social media use and overload. Using a survey of 282 enterprise social media users in the workplace as a basis, we find an inverted U-shaped relationship between work-related enterprise social media use and information overload and between work-related enterprise social media use and social overload. Moreover, a U-shaped relationship is found between social-related enterprise social media use and information overload and between social-related enterprise social media use and social overload. Communication visibility positively moderates the inverted U-shaped relationships between work-related enterprise social media use and information overload and between work-related enterprise social media use and social overload, but negatively moderates the U-shaped relationship between social-related enterprise social media use and information overload. The theoretical and practical implications are also discussed.

Collaborative filtering (CF) has been applied in various domains to resolve problems related to information overload. In a knowledge-intensive environment, most works are processed through teamwork. A user on a team can reference task-related documents from other trusted members to support work on the task. However, the traditional personalised recommender systems no longer meet the demand of teams or groups. Therefore, this work proposes a novel document recommendation method based on a group-based trust model. Our method will analyse the degrees of trust among users in a group and then identify the trustworthy users. The proposed group trust consists of a hybrid personal trust (HPT) model and users’ importance (i.e. users’ activity, similarity and reputation) in a group. Group-based trust is then integrated with the user-based CF to recommend documents to users. The experiments demonstrate that the proposed method can provide better performance than other trust-based recommendation methods; it not only obtains reliable trust values to increase the accuracy of predictions but also enhances the recommendation quality.

Media plays a crucial role in information dissemination during significant social, economic, political events and crises, including epidemics Public look upon the media for credible and authentic information during such times resulting in a surge in information seeking In 1976, Sandra Ball-Rokeach and Melvin DeFleur proposed media dependency theory (Lin,2020) Audience dependency on the media increased with the rise in social conflicts, resulting in greater chances of the media’s potential effect During epidemics, media is known to spread awareness and disease mitigation efforts (Xiao et al , 2015) But in the digital age, information overload, misinformation, and rumours tend to be detrimental to such mitigation efforts The Director-General of WHO (2020) stressed the importance of facts, stating that misinformation makes health workers’ efforts challenging While social media platforms have been asked to screen fake news, the influencers have been asked to actively promote facts in their posts, as some of the measures to tackle the ‘ infodemic’ regarding COVID-19 This study uses the concept of media literacy, active audience, media dependency theory, health information-seeking behaviour, expectancy-value theory, among others, to recognize information search patterns and assess media literacy levels, including processing and verification of information by mainstream media audiences and social media users during the COVID-19 pandemic period in India © Media Watch

Consumers are increasingly using social media to interact with other consumers about health conditions and treatment options. This study aimed to investigate the advantages and disadvantages of using social media for health-related purposes from the consumers’ perspectives. Five focus groups with 36 Australian adults with a chronic condition and on medication were conducted, audio-recorded, transcribed verbatim, and thematically analysed. Consumers reported that social media was very convenient, for accessing health-related information and for peer engagement; user-friendly; improved their health knowledge; empowered them; and provided social and emotional support. The disadvantages included information overload, wasting time; negative feelings; doubts about online information credibility; and issues related to online interactions. Despite some disadvantages, health-related use of social media led consumers to feel supported, knowledgeable, and empowered. Consumers’ motivation to keep accessing social media for health-related purposes opens up avenues for the delivery of services via social media.

With the advent of technology, a greater amount of information is available in a greater variety of formats that are accessible through a greater variety of media and communication channels, resulting in a much more complex and rich information environment for business managers. Many businesses are seeing the development of big data as unique opportunity and also experience it as demanding in terms of managerial skills and organisational capability to deal with it. Existing literature provides managerial prescriptions and systemic guidelines to make use of this information, but does not provide empirical evidence on how practising managers actually deal with information overload and make sense of the available data. This article discusses the findings from an interpretive case study of five organisations from the hotel industry within the hospitality sector. It was found that the volume and pace coupled with the qualitative and unsolicited nature of information caused information overload to managers. To cope with this phenomenon at personal level, managers used a combination of filtering, withdrawal and summarising strategies. At organisational level, the practice of summarising evolved into development and use of interactive dashboards.

Data overload, especially in the visual channel, represents a major challenge with regards to display design in data-rich domains. One promising means of addressing data overload is with the use of eye tracking technology to better understand an operator’s transition methods between tasks in order to support operators in real-time. The goal of this study is to develop a Markovian framework analyzing eye movement across different panels while performing a simulated Unmanned Aerial Vehicle (UAV) control task, the chosen application of this study. Across ten participants, an increase in workload adversely affected performance, but did not change individual scan patterns, which were based on a Markovian framework. However, across participants, eye tracking data revealed five distinct scan patterns, each with varying levels of success in terms of response time and accuracy. The top four performers all adopted different scan patterns. The findings show that eye tracking can provide unique insights to explain performance differences between individuals. Overall, the findings provide the foundation for developing an algorithm that optimizes performance while accounting for individual differences.

Today, complaints about information overload – associated with an overwhelming deluge of data – are commonplace. Early modernists have reacted to these concerns by showing that similar ones have arisen before. While this perspective is useful, it leaves out what was novel about the concept of information overload, which relied on a historically specific model of the human being. I trace the term’s history back to 1960, when the American psychologist and systems theorist James Grier Miller published his article on ‘information input overload and psychopathology’. In Grier Miller’s usage, the idea of information overload signalled as much a reconceptualization of human beings as communication channels whose capacity could be overwhelmed as it did concerns about the volume of reading material to manage. Through his work, and the broader subsequent adoption of the term in academic and journalistic venues, I show how ‘information overload’ reflected intellectual and social trends specific to its time.

This study focuses on the ironic situation in which news is more available than ever but people are becoming overwhelmed and thus avoid it. A theoretical model is suggested to investigate the relationships between perceived news overload and its cognitive and attitudinal consequences among South Korean Internet users. A structural model reveals that perceived news overload induced news avoidance by increasing news fatigue and news analysis paralysis. Furthermore, this study finds evidence that news consumers are willing to use news curation services to alleviate news avoidance and thus stay informed.

This study examines the information behavior of Black immigrants in the United States and specifically investigates possible linkages between information overload and acculturative stress. Focus groups were conducted with African, Afro-Caribbean, and Afro-Latinx immigrants in Florida. When analyzed according to Jaeger and Burnett’s theory of information worlds (Burnett and Jaeger, 2011; Jaeger and Burnett, 2010), the data supports that participants experience information overload as a result of the voluminous and dispersed nature of information in the US; perceptions of belonging and transnationality; and undertaking high-stakes tasks such as immigration procedures, finding employment, and understanding cultural norms. Participants felt that the large, stratified, and complex US information landscape can prompt stress. Since information overload poses a barrier to immigrant social inclusion, it can be interpreted as acculturative stress.

People surfing the Internet are faced with an onslaught of messages from multiple sources, which can overwhelm receivers. In contrast to previous studies, which have used ‘choice overload’ to represent the amount of information provided to consumers, this study used ‘information overload’ theory to represent the abundance of information received by consumers in online shopping environments. Borrowing from the concepts of the communication model, this study investigated the antecedents of perceived information overload, including information characteristics (message), the information source, the system interface (channel) and recipients’ motivation (receiver). A total of 15 adults with more than 3 years of online shopping experience participated in a focus group discussion. By integrating focus group results and the results of previous studies into a theoretical framework, this study developed and empirically tested a structural equation model of online information overload among 456 PChome customers. The results indicated that the complexity and ambiguity of information characteristics, number of brand alternatives offered by the information source and system interface all positively affect consumers’ perceived information overload. Furthermore, information recipients’ motivation not only negatively affected consumers’ perceived information overload but also moderated the relationship between the number of brand alternatives and consumers’ perceived information overload.

Modern sensors for health surveillance generate high volumes and rates of data that currently overwhelm operational decision-makers. These data are collected with the intention of enabling front-line clinicians to make effective clinical judgments. Ironically, prior human–systems integration (HSI) studies show that the flood of data degrades rather than aids decision-making performance. Health surveillance operations can focus on aggregate changes to population health or on the status of individual people. In the case of clinical monitoring, medical device alarms currently create an information overload situation for front-line clinical workers, such as hospital nurses. Consequently, alarms are often missed or ignored, and an impending patient adverse event may not be recognized in time to prevent crisis. One innovation used to improve decision making in areas of data-rich environments is the Human Alerting and Interruption Logistics (HAIL) technology, which was originally sponsored by the US Office of Naval Research. HAIL delivers metacognitive HSI services that empower end-users to quickly triage interruptions and dynamically manage their multitasking. HAIL informed our development of an experimental prototype that provides a set of context-enabled alarm notification services (without automated alarm filtering) to support users’ metacognition for information triage. This application is called HAIL Clinical Alarm Triage (HAIL-CAT) and was designed and implemented on a smartwatch to support the mobile multitasking of hospital nurses. An empirical study was conducted in a 20-bed virtual hospital with high-fidelity patient simulators. Four teams of four registered nurses (16 in total) participated in a 180-minute simulated patient care scenario. Each nurse was assigned responsibility to care for five simulated patients and high rates of simulated health surveillance data were available from patient monitors, infusion pumps, and a call light system. Thirty alarms per nurse were generated in each 90-minute segment of the data collection sessions, only three of which were clinically important alarms. The within-subjects experimental design included a treatment condition where the nurses used HAIL-CAT on a smartwatch to triage and manage alarms and a control condition without the smartwatch. The results show that, when using the smartwatch, nurses responded three times faster to clinically important and actionable alarms. An analysis of nurse performance also shows no negative effects on their other duties. Subjective results show favorable opinions about utility, usability, training requirement, and adoptability. These positive findings suggest the potential for the HAIL HSI system to be transferrable to the domain of health surveillance to achieve the currently unrealized potential utility of high-volume data.

Information overload has long been studied as a phenomenon that causes problems at the personal, social and organisational level. This study investigates overload from a new angle, that of the influence of age on perceptions of information overload. A combination of questionnaires, interviews and diaries were used to gain insight into people’s perceptions towards information overload. It was found that people of all ages suffer from information overload but young people are primarily affected by information literacy levels while older people are affected by technology. There was evidence of a link between age and technology use. A link was also found between job role and information overload and the impact technology has had on the quantity of information available. This research will benefit anyone, either individually or within an organisation, looking for ways to combat information overload. It identifies the influence of age on various factors and recommends actions that may be taken to reduce information overload. In particular, recommendations were made for further training in technology and information literacy. The paper is based on an approach not seen before in the literature as it investigates the effects of age on information overload by seeking to understand how perceptions towards information overload may differ between different age groups. It is anticipated that this paper will trigger further studies that could focus on the effect of job role on information overload and the likelihood of information addiction becoming a future concern.

In consultation with the U.S. Centers for Disease Control and Prevention’s Center for Global Health (CDC CGH), this study compared narrative and non-narrative message designs for global public health initiative issues management. A multiple-message experimental design prompted participants ( N = 669) to read a message about a CDC CGH initiative, and measured perceptions of agency reputation, support for a global public health mission, and intentions to share information. Narrative message design had direct effects on intentions to share the message interpersonally and through social media and indirect effects on the outcomes through perceptions of message features and mediating states (i.e., story structure, understanding, personal relevance, information overload) and transportation. The study contributes to theory and practice by confirming the mediating role of transportation, building on a message features approach to the study of narrative persuasion, and speaking to the challenges of issues management in global public health.

Self-efficacy in getting information, which is defined as individuals’ judgments of their own capabilities to search, compare and evaluate information they need, is critical given the negative effects of information overload in the modern information society. This study focuses on digital library users with the purpose of identifying the user groups with lower levels of self-efficacy in getting information so as to provide insights for targeted user training. Specifically, this study explores the effect of individual differences on self-efficacy in getting information in terms of gender, current position, field and experience with using the digital library. The findings suggest that there are no significant differences between male and female users regarding self-efficacy in getting information. Undergraduate students as well as master or doctoral students and the users coming from the fields of arts and humanities as well as social sciences perceive lower levels of self-efficacy in getting information. The users who have longer experience with using the digital library perceive higher levels of self-efficacy in getting information. These findings and implications are discussed.

Past research has found that older US adults (aged 50–75 years) exhibit high levels of cancer information overload and cancer worry; however, no study to date has examined whether these perceptions are related to information seeking/scanning. To explore this relationship, older adults ( N = 209, Mage = 55.56, SD = 4.24) were recruited to complete a survey measuring seeking, scanning, cancer information overload, and cancer worry. Most participants were high-scan/seekers (40.2%) followed by low-scan/seekers (21.1%), high-scan/no seekers (19.6%), and low-scan/no seekers (19.1%). Low-scan/no seekers had significantly higher cancer information overload compared to all other groups, consistent with the postulate that overload and seeking/scanning are negatively related. Low-scan/no seekers and high-scan/seekers both exhibited higher cancer worry severity, consistent with past research suggesting that cancer worry explains high levels of activity/inactivity.

This Association of Survey Computing (ASC) conference was interested in exploring how the concept of "research data" is changing and discovering the ways practitioners are getting to grips with the many challenges and opportunities thrown up by this data revolution. This article showcases a presentation by Jon Puleston -- VP of Innovation of Lightspeed GMI at Kantar business -- that investigates the science of visual communication and examines the role icons, charts and visuals play in the gathering and delivery of research data. Amongst other things, it discusses how we process visual information, how visuals help us to remember information and how visuals motivate us to consume information. It also provides best practice advice for using icons and charts in research and guidance on how to exploit visuals when delivering research information.

Deal of the day is a form of e-commerce in which an intermediary allows merchants access to a subscriber list, to promote their offerings at a discount. This study performs a cluster analysis on the purchase history of a deal intermediary, to identify customer segments based on their purchase frequency, price sensitivity and the types of deal they buy. Five segments were identified, including a large group of customers who made one purchase and then stopped buying, a small group of extremely deal-prone subscribers, and a segment that limits their purchases to very few types of product (e.g. restaurant meals or spa treatments). The findings further show that targeting deals to specific customers may be desirable in the future to prevent information overload and ensure loyalty.

Among the applications of Web 2.0, social networking sites continue to proliferate and the volume of content keeps growing; as a result, information overload causes difficulty for users attempting to choose useful and relevant information. To resolve this problem, most researches only utilize users’ preferences, the content of items or social influence to make recommendations. However, people’s preferences for items may be affected by social friends, personal interest and item popularity. Moreover, each factor has a different impact on each user. In this work, we propose a novel recommendation method based on different types of influences: social, interest and popularity, using personal tendencies in regard to these factors to recommend photos in a photo-sharing website, Flickr. The personal tendencies related to these three influences are regarded as personalized weights to combine influence scores for predicting the scores of items. The experimental results show that our proposed methods can improve the quality of recommendations.

Visual data overload and associated performance breakdowns in safety-critical environments have triggered a significant interest in developing multimodal displays, i.e., displays that distribute information across multiple sensory channels (mainly vision, hearing, and touch). Yet, more than 95% of studies on multimodal information processing suffer from a methodological shortcoming: the failure to perform ‘crossmodal matching’ where participants equate the perceived intensities of stimuli across sensory channels in advance of an experiment, with the goal to avoid confounding modality with salience. Currently, there is no agreed-upon technique for performing this task, and the few studies that included this step employed different methods. The goal of this study is to compare three crossmodal matching techniques to determine whether they result in useful and congruent outcomes. In particular, the degree of intra-individual variability of crossmodal matches is of interest. Eighteen participants performed a series of 54 crossmodal matches for visual, auditory, and tactile stimuli. They used a mouse and visual sliding scale, keyboard arrows, or a rotary knob to adjust intensity. Intra-individual variability of matches differed significantly as a function of matching technique and the order in which stimuli are presented. These findings confirm the need for developing an agreed-upon reliable crossmodal matching technique for use in future studies.

The author explores the concept of ‘information anorexia’ – the idea that one may not be receiving the essential information one needs to be an effective information professional. In the article, the author outlines a construct of information anorexia and its causes, illustrates some factors that might lead to information anorexia, and puts forth some thoughts and practices on coping with it in the professional and personal realm.

An increasing number of companies use social media such as micro blogs to promote celebrities in Internet communities. Companies may run their official micro blogs differently, which in turn leads to different public engagements on micro blogging sites. This study takes a perspective on the adoption behaviours of micro blogs in enterprises by looking at the relationship between media frame and audience frame based on the China Fortune 500 firms in 2014. The results show that the updates, active days and followings are associated with public engagement with the corporate official micro blogs. In particular, we found information overload from information updates. The marginal utility of the public engagement decreases as number of updates increases. The results also show that the daily variance of updates has a significant influence on the audience frame.

Based on the conceptual analysis, the study examines the features of cognitive barriers and their impact on information seeking. The study resulted in a typology specifying six sub-types of cognitive barriers: unwillingness to see one’s needs as information needs, inability to articulate one’s information needs, unawareness of information sources, low self-efficacy, poor search skills and inability to deal with information overload. The sub-types were reviewed at two stages of the information-seeking process: identifying and articulating information needs; and selecting and accessing information sources. The impact of cognitive barriers is mainly negative because they block, limit or hamper information seeking, or give rise to negative reactions such as frustration. Cognitive barriers can also impact positively by helping the individual to concentrate on a few, good enough sources of information.

Content creation is no longer the exclusive domain of journalists, newspapers and advertisers. As Clay Shirky1 has famously pointed out, publishing is no longer a job or an industry, it’s a button. We’re all creating content, as originators or commentators, which is then shared and re-shared many times over. The resulting cascade of information requires new content organization and consumption techniques, and the disciplines, competencies and skills of content curation are now critical. This article argues that effective content curation requires real-time technology and tools used by knowledge domain experts who can interpret and add insight to content. It explores the content curation process, introduces five laws for the curation economy, presents models of content curation and assesses the essential curation skills.

One promising means of overcoming data overload in complex domains is through the introduction of tactile displays, which can offload the overburdened visual channel. However, the effectiveness of tactile displays depends on taking into consideration attentional systems and the limitations of the human perception. One important question is the extent to which the tactile modality is susceptible to change blindness, i.e. the failure to detect even large and expected changes when these changes coincide with a “transient” stimulus. Recent research has demonstrated an analog of change blindness in the tactile modality for pattern change recognition. The present study examined whether tactile change blindness, as well as crossmodal visual-tactile change blindness, occurs in the context of search and monitoring tasks, and whether it is affected by the addition of a secondary task. The application domain for this experiment was simulated Unmanned Aerial Vehicle control. The findings confirmed the occurrence of tactile change blindness; however, no crossmodal change blindness was observed and change detection was unaffected by the addition of a secondary search task. Overall, this research add to the knowledge base in multimodal and redundant information processing and can inform the design of multimodal displays for complex, data-rich domains.

Intelligence analysts—overloaded with complex and disparate data—must incorporate information into cohesive and convincing narratives and explanations. For analysts, data overload can result in developing premature conclusions and limit their ability to effectively conduct comprehensive analyses. Historically, automated decision aids designed to help with these processes have largely failed analysts in managing a fundamental work tradeoff between analytic narrowing and broadening because software tools too often attempt to supplant analyst reasoning, rather than support the iterative process as a whole. Instead of such brittle approaches, previous research suggests analysts would benefit from automation that supports a collaborative partnership throughout the analysis process. The research and development described in this work began with a cognitive analysis of practicing analysts, entailing literature review, interviews, and walkthroughs with a software prototype. Findings from the cognitive analysis were translated into design requirements for decision aids that support representation management across multiple intelligence products. The findings provide insight into under-supported cognitive and collaborative work in modern intelligence analysis with implications for the future design of useful automated decision aids.

Information managers are now bombarded with information from multiple sources: traditional media, the Internet and more recently social media. The demand for fast insight from this data is becoming the primary challenge for those tasked with managing information for business advantage. This article explores how the consumption, analysis and delivery of insight from content are changing and how this will impact information managers in the future.

In the context of modern defense and security operations, analysts are faced with a continuously growing set of information of different nature that causes significant information overload problems and prevents developing good situation awareness. Fortunately, Visual Analytics (VA) has emerged as an efficient way of handling and making sense of massive datasets by exploiting interactive visualization technologies and human cognitive abilities. Defence R&D Canada has conducted a review of the applicability of VA to support military and security operations. This paper is meant to provide someone new to this area with a quick overview of the current state of the art in VA. We introduce the important scientific visualization, interaction and reasoning concepts supporting VA, followed by VA advanced techniques. Then, we describe how VA can contribute to the cyber security and intelligence analysis application domains, along with promising research projects and commercial software. Finally, we discuss the future of VA research.

Individual differences in the capacity for information processing in complex tasks can be predicted from both personality and temperament that derive from both the biological and social substrates of human development and behavior. If there are cultural differences in brain structure and function that govern information processing, then two different cultures may show biologically based temperamental differences in sensitivity to stimulation (e.g., Pavlov’s Strength of the Nervous System) which in turn may predict individual differences in capacity for tolerating environmentally determined stimulus overloads. We examined the relationship between biologically based measures of Pavlovian Temperament (Strength of Excitation, Inhibition, and Mobility) and an individual differences measure consisting of five dimensions of capacity for tolerating information load. Both direct and indirect effects of country of origin on capacity for information processing were tested in a mediated path analytic model in which Pavlovian Excitation, Inhibition, and Mobility were hypothesized to mediate the relationship between culture and self-reported information processing capacities.

Computational models of attention can be used to mitigate data overload especially when multiple sensors provide feeds to a human observer who is not present in the same environment as the network of sensors. Computational models of attention use a variety of functional components to find a balance between reorienting to new events and stimuli and focusing on currently active and relevant events by guiding one or more sampling processes. This research reports the results from tests of the performance of several functional components of one computational attention model that has been designed to address overload from multiple sensor feeds. The functional components tested include parallel center and surround sampling processes, exploratory drive, and temporal dependencies. The tests map algorithm sampling behavior over its parameter space independent of environmental input – establishing baseline performance prior to testing performance when multiple objects move and new events occur.

To address issues in enterprise systems, operations research (OR) analysts need to be able to understand, codify, and communicate various aspects of the issues, such as the environment’s conditions and their relationships. Models are a natural way to capture that information, but they must be understandable to a variety of stakeholders involved in improving the enterprise. At the same time, the large amount of available information, such as event history and weather data, can easily overload analysts. To help analysts cope with data overload, it is useful for models to be accessible to computational tools that can provide data processing and visualization capabilities. To support both of those goals simultaneously, we describe an approach that supports the elicitation of qualitative insight from operations researchers and other relevant stakeholders and also provides avenues for computer software to perform semantic labeling and quantitative data processing. This approach directly supports an iterative OR process that satisfies the needs of multiple stakeholder communities, enabling initial qualitative relationships and hypotheses to be further investigated and justified with data-driven conclusions. Building on our previous experiences in knowledge acquisition and quantitative analysis, this paper outlines a new integrated workflow and a collection of graphical representation concepts for operations research and similar domains.

This article examines the origins of psychology's adoption of a standardized style and format for its publications and the controversies that this decision engendered. The present account draws on perspectives derived from the history of reading and the sociology of professions to explain the historical appeal of such standards. Archival documents are used to trace the events that led to the drafting of the first set of publication standards in 1929. Where previous historical accounts of the publication manual have stressed the influence of behaviorism, the discipline's leaders embraced these instructions because of the perception of information overload resulting from the rapid expansion and professionalization of psychology following World War I. Under the auspices of the National Research Council, a committee on publication practices surveyed scientists, editors, and publishers in the hopes of making more efficient the communication of psychological knowledge within an increasingly large and anonymous discipline. Archival documents also reveal an animated debate over whether the progress of psychology as a science required the adoption of universally followed rules trusted by all or the cultivation of the scientist's creativity and individuality of expression.

Iterative, opportunistic and evolving visual sense-making has been an important research topic as it assists users in overcoming ever-increasing information overload. Exploratory visualization systems (EVSs) maximize the amount of information users can gain through learning and have been widely used in scientific discovery and decision-making contexts. Although many EVSs have been developed recently, there is a lack of general guidance on how to evaluate such systems. Researchers face challenges such as understanding the cognitive learning process supported by these systems. In this paper, we present a formal user study on Newdle, a clustering-based EVS for large news collections, shedding light on a general methodology for EVS evaluation. Our approach is built upon cognitive load theory, which takes the user as well as the system as the focus of evaluation. The carefully designed procedures allow us to thoroughly examine the user’s cognitive process as well as control the variability among human subjects. Through this study, we analyse how and why clustering-based EVSs benefit (or hinder) users in a variety of information-seeking tasks. We also summarize leverage points for designing clustering-based EVSs.

The author looks at the concept of ‘information obesity’ – analogous to physical obesity – especially as it applies to information professionals. The author examines causes, such as information overload, and additional factors that make information professionals prone to information obesity. The article concludes with practical and philosophical suggestions for preventing and coping with information obesity, and an overview of ideas around the concept of ‘slow information’.