The one-day workshop is led by 5 researchers, and it will accommodate up to 32 participants. Qian Zhao, Gediminas Adomavicius, F. Current recommender systems often show the same most-highly recommended items again and again ignoring the feedback that users neither rate nor click on those items. We conduct an online field experiment to test two ways of manipulating top-N recommendations with the goal of improving user experience: cycling the top-N recommendation based on their past presentation and serpentining the top-N list mixing the best items into later recommendation requests.
We find interesting tensions between opt-outs and activities, user perceived accuracy and freshness. Cycling within the same session might be a "love it or hate it" recommender property because users in it have a higher opt-out rate but engage in more activities. Cycling across sessions and serpentining increase user activities without significantly affecting opt-out rates.
Users perceive more change and freshness but less accuracy and familiarity. Combining cycling and serpentining does not work as well as each individual manipulation separately. These two ways of manipulations on top-N list demonstrate some attractive properties but also call for innovative approaches to overcome their potential costs.
Productive and dedicated members are critical to the success of online production communities like Wikipedia. Many communities organize in subgroups where members voluntarily work on projects of shared interest. In this paper, we investigate how members' pre-joining connections with the subgroup predict their productivity and withdrawal after joining.
Analyses of 79, editors in 1, WikiProjects show that 1 both identity-based and bonds-based attachment increased editors' post-joining productivity and reduced their likelihood of withdrawal; 2 identity-based attachment had a stronger effect on boosting direct contributions to articles while bonds-based attachment had a stronger effect on increasing article and project coordination, and reducing member withdrawal.
Wikipedia-based studies and systems frequently assume that no two articles describe the same concept. However, in this paper, we show that this article-as-concept assumption is problematic due to editors' tendency to split articles into parent articles and sub-articles when articles get too long for readers e. In this paper, we present evidence that this issue can have significant impacts on Wikipedia-based studies and systems and introduce the sub-article matching problem.
The academic, economic and societal impacts of Open Access: an evidence-based review
The goal of the sub-article matching problem is to automatically connect sub-articles to parent articles to help Wikipedia-based studies and systems retrieve complete information about a concept. We then describe the first system to address the sub-article matching problem. We show that, using a diverse feature set and standard machine learning techniques, our system can achieve good performance on most of our ground truth datasets, significantly outperforming baseline approaches.
Sustaining our community. Loren Terveen and Aaron Quigley. Molly A. International Journal of Human—Computer Interaction 32, 4: — A broad-based research team developed a Health Insurance Portability and Accountability Act HIPAA -compliant educational website for women with ovarian cancer to improve the quality of supportive oncology care. Prior to a randomized clinical trial of the website, initial usability testing was implemented to evaluate the website. Major issues thought to potentially impede actual usage were prioritized in redevelopment and the second usability review, conducted by the same expert, saw an improvement in scores.
Incorporating usability concepts from the start of development, fulfilling the positive expectations of end-users, and identifying the technical and personal factors that optimize use may greatly enhance the usage of health websites. International Journal of Human-Computer Interaction 32, 4: — Svetlana Yarosh and Shankar Krishnan. System and method for providing separate communication zones in a large format videoconference.
A system that incorporates the subject disclosure performs, for example, displaying a video image of a remote scene at a display surface, wherein the remote scene is remote from the display surface. Overlapping video images are obtained from different vantage points of a local scene observable from the display surface.
A composite video image is generated of the local scene from the video images and forwarded to the remote location. A first audio signal is generated representing first sounds associated with a first region of the local scene without representing other sounds associated with a second region of the local scene. The first audio signal is forwarded to audio processing equipment at the remote location to present the first sounds at a first region of the remote scene at the remote location without presenting the first sounds at a second region of the remote scene.
Other embodiments are disclosed. Prior work relevant to incorporating personality into recommender systems falls into two categories: social science studies and algorithmic ones. Social science studies of preference have found only small relationships between personality and category preferences, whereas, algorithmic approaches found a little improvement when incorporating personality into recommendations.
As a result, despite good reasons to believe personality assessments should be useful in recommenders, we are left with no substantial demonstrated impact. In this work, we start with user data from a live recommender system, but study category-by-category variations in preference both rating levels and distribution across different personality types. By doing this, we hope to isolate specific areas where personality is most likely to provide value in recommender systems, while also modeling an analytic process that can be used in other domains. After controlling for the family-wise error rate, we find that High Agreeableness users rate at least 0.
We also find differences in consumption in four different personality types between people who manifested high and low levels of that personality. Providing pedestrian navigation instructions on small screens is a challenging task due to limited screen space. As image-based approaches for navigation have been successfully proven to outperform map-based navigation on mobile devices, we propose to bring image-based navigation to smartwatches.
We contribute a straightforward pipeline to easily create image-based indoor navigation instructions that allow users to freely navigate in indoor environments without any localization infrastructure and with minimal user input on the smartwatch. In a user study, we show that our approach outperforms the current state-of-the art application in terms of task completion time, perceived task load and perceived usability. In addition, we did not find an indication that there is a need to provide explicit directional instructions for image-based navigation on small screens.
Qian Zhao, Shuo Chang, F. Gaze Prediction for Recommender Systems. As users browse a recommender system, they systematically consider or skip over much of the displayed content. It seems obvious that these eye gaze patterns contain a rich signal concerning these users' preferences. However, because eye tracking data is not available to most recommender systems, these signals are not widely incorporated into personalization models. In this work, we show that it is possible to predict gaze by combining easily-collected user browsing data with eye tracking data from a small number of users in a grid-based recommender interface.
Our technique is able to leverage a small amount of eye tracking data to infer gaze patterns for other users. We evaluate our prediction models in MovieLens -- an online movie recommender system. Our results show that incorporating eye tracking data from a small number of users significantly boosts accuracy as compared with only using browsing data, even though the eye-tracked users are different from the testing users e.
Qian Zhao, Zihong Huang, F. Maxwell F. We introduce a theoretical framework called precision crowdsourcing whose goal is to help turn online information consumers into information contributors. The framework looks at the timing and nature of the requests made of users and the feedback provided to users with the goal of increasing long-term contribution and engagement in the site or system. We found that asking increases tags provided overall, though asking generally decreases the provision of unprompted tags.
Users were more likely to comply with our request when we asked them to tag obscure movies and when we used reciprocal request rhetoric. Shuo Chang, F. Maxwell Harper, and Loren Gilbert Terveen. The gender gap in Wikipedia's content, specifically in the representation of women in biographies, is well-known but has been difficult to measure.
Furthermore the impacts of efforts to address this gender gap have received little attention. To investigate we utilise Wikidata, the database that feeds Wikipedia, and introduce the "Wikidata Human Gender Indicators" WHGI , a free and open source, longitudinal, biographical dataset monitoring gender disparities across time, space, culture, occupation and language.
Through these lenses we show how the representation of women is changing along 11 dimensions. Furthermore, to demonstrate its general use in research, we revisit previously published findings on Wikipedia's gender bias that can be strengthened by WHGI. Do It for the Viewers! Online user-generated video sharing communities, such as YouTube, are becoming more popular than conventional studio-produced content. These communities provide every user with the opportunity to create and promote their own video contenta compelling venue for children and teenagers to share their stories and voices.
In this study, we investigate the practices of youth video creators on YouTube. To do so, we conducted a content analysis of the audience engagement practices of youth author channels, comparing them to adult and professional YouTubers when appropriate. We found that most youth authors are aware of and actively engage with their imaginary or real audiences on YouTube. They emulate the conversational and audience engagement practices seen in professional quality YouTube channels, but may not have the video editing or other meta-content skills or experience to do so.
Based on our findings, we point to a number of implications for future research and design in this space. Raghav Pavan Karumur and Joseph A.
In this work, we explore the degree to which personality information can be used to model newcomer retention, investment, intensity of engagement, and distribution of activity in a recommender community. Prior work shows that Big-Five Personality traits can explain variation in user behavior in other contexts. Building on this, we carry out and report on an analysis of MovieLens users with identified personality profiles.
We find that Introverts and low Agreeableness users are more likely to survive into the second and subsequent sessions compared to their respective counterparts; Introverts and low Conscientiousness users are a significantly more active population compared to their respective counterparts; High Openness and High Neuroticism users contribute tag significantly more compared to their counterparts, but their counterparts consume browse and bookmark more; and low Agreeableness users are more likely to rate whereas high Agreeableness users are more likely to tag.
These results show how modeling newcomer behavior from user personality can be useful for recommender systems designers as they customize the system to guide people towards tasks that need to be done or tasks the users will find rewarding and also decide which users to invest retention efforts in. Emoji are commonly used in modern text communication. However, as graphics with nuanced details, emoji may be open to interpretation.
Emoji also render differently on different viewing platforms e. We explore whether emoji renderings or differences across platforms give rise to diverse interpretations of emoji. Both in terms of sentiment and semantics, we analyze the variance in interpretation of the emoji, quantifying which emoji are most and least likely to be misinterpreted. When considering renderings across platforms, these disagreements only increase. Overall, we find significant potential for miscommunication, both for individual emoji renderings and for different emoji renderings across platforms.
What kinds of content do children and teenagers author and share on public video platforms? We approached this question through a qualitative directed content analysis of over youth-authored videos filtered by crowdworkers from public videos on YouTube and Vine. We found differences between YouTube and Vine platforms in terms of the age of the youth authors, the type of collaborations witnessed in the videos, and the significantly greater amount of violent, sexual, and obscene content on Vine.
We also highlight possible differences in how adults and youths approach online video sharing. Specifically, we consider that adults may view online video as an archive to keep precious memories of everyday life with their family, friends, and pets, humorous moments, and special events, while children and teenagers treat online video as a stage to perform, tell stories, and express their opinions and identities in a performative way. Families are becoming more culturally heterogeneous due to a rise in intermarriage, geographic mobility, and access to a greater diversity of cultural perspectives online.
Investigating the challenges of cross-cultural parenting can help us support this growing demographic, as well as better understand how families integrate and negotiate advice from diverse online and offline sources in making parenting decisions. We interviewed parents from 18 families to understand the practices they adopt to meet the challenges of cross-cultural parenting.
We investigated how these families respond to conflicts while integrating diverse cultural views, as well as how they utilize the wealth of parenting resources available online in navigating these tasks. We identify five themes focused on how these families find and evaluate advice, connect with social support, resolve intra-family tensions, incorporate multicultural practices, and seek out diverse views. Based on our findings, we contribute three implications for design and translations of these implications to concrete technology ideas that aim to help families better integrate multiple cultures into everyday life.
Baris Unver, Sarah A. Projector-camera pro-cam systems create virtual environments for remote interaction with audio and video support. However, previous pro-cam systems require custom hardware and thus have not been used at-scale in the field. In this work, we present a pro-cam application to reinforce social relationships for an off-the-shelf pro-cam system. The ShareTable application users can use video chat in conjunction with sharing tabletop video, allowing them to connect while playing and interacting together. Friendsourcing consists of broadcasting questions and help requests to friends on social networking sites.
Despite its potential value, friendsourcing requests often fall on deaf ears. One way to improve response rates and motivate friends to undertake more effortful tasks may be to offer extrinsic rewards, such as money or a gift, for responding to friendsourcing requests. However, past research suggests that these extrinsic rewards can have unintended consequences, including undermining intrinsic motivations and undercutting the relationship between people.
To explore the effects of extrinsic reward on friends' response rate and perceived relationship, we conducted an experiment on a new friendsourcing platform - Mobilyzr. Results indicate that large extrinsic rewards increase friends' response rates without reducing the relationship strength between friends. Additionally, the extrinsic rewards allow requesters to explain away the failure of friendsourcing requests and thus preserve their perceptions of relationship ties with friends.
Isaac L. Wikipedia articles about places, OpenStreetMap features, and other forms of peer-produced content have become critical sources of geographic knowledge for humans and intelligent technologies. We find that in both Wikipedia and OpenStreetMap, peer-produced content about rural areas is of systematically lower quality, is less likely to have been produced by contributors who focus on the local area, and is more likely to have been generated by automated software agents i.
We then codify the systemic challenges inherent to characterizing rural phenomena through peer production and discuss potential solutions. The lack of certain types of geographic data prevents the development of location-aware technologies in a number of important domains. One such type of "unmapped" geographic data is space usage rules SURs , which are defined as geographically-bound activity restrictions e. Researchers in the area of human-computer interaction have recently begun to develop techniques for the automated mapping of SURs with the aim of supporting activity planning systems e.
This paper also contributes a series of new SUR benchmark datasets to help further research in this area. Geotagged tweets and other forms of social media volunteered geographic information VGI are becoming increasingly critical to many applications and scientific studies. An important assumption underlying much of this research is that social media VGI is "local", or that its geotags correspond closely with the general home locations of its contributors. In addition, we show that the geographic contours of localness follow important sociodemographic trends, with social media in, for instance, rural areas and older areas, being substantially less local in character when controlling for other demographics.
We demonstrate through a case study that failure to account for non-local social media VGI can lead to misrepresentative results in social media VGI-based studies. Finally, we compare the methods for determining localness, finding substantial disagreement in certain cases, and highlight new best practices for social media VGI-based studies and systems. Michael D. Ekstrand and Michael Ludwig. The Journal of Object Technology 15, 1: The dependency injection design pattern improves the configurability, testability, and maintainability of object-oriented applications by decoupling components from both the concrete implementations of their dependencies and the strategy employed to select those implementations.
In recent years, a number of libraries have emerged that provide automated support for constructing and connecting dependency-injected objects. Our experience developing systems with these tools has led us to identify two shortcomings of existing dependency injection solutions: the mechanisms for specifying component implementations often make it difficult to write and configure systems of arbitrarily-composable components, and the toolkit implementations often provide limited capabilities for inspection and static analysis of the object graphs of dependency-injected systems.
We present Grapht, an new dependency injection container for Java that addresses these issues by providing context-aware policy, allowing component implementation decisions to depend on where in the object graph a component is required, and using a design that allows for static analysis of configured object graphs. To achieve its objectives, Grapht is built on a mathematical representation of dependency injection and object graphs that facilitates static analysis and straightforward implementation, and forms a basis for further consideration of the capabilities of dependency injection.
The mathematical representation includes context-aware policy that we show to be strictly more expressive than the qualified dependencies used in many current toolkits. We demonstrate the utility of our approach with a case study showing how Grapht has aided in the development of the LensKit recommender systems toolkit. Recommender systems face several challenges, e. Where algorithms struggle, people may excel. We therefore designed CrowdLens to explore different workflows for incorporating people into the recommendation process. We did an online experiment, finding that: compared to a state-of-the-art algorithm, crowdsourcing workflows produced more diverse and novel recommendations favored by human judges; some crowdworkers produced high-quality explanations for their recommendations, and we created an accurate model for identifying high-quality explanations; volunteers from an online community generally performed better than paid crowdworkers, but appropriate algorithmic support erased this gap.
We conclude by reflecting on lessons of our work for those considering a crowdsourcing approach and identifying several fundamental issues for future work. Organizational scholars disagree about how much a recipient unit should modify a best practice when incorporating it.
Some evidence indicates that modifying a practice that has been successful in one environment will introduce problems, undercut its effectiveness and harm the performance of the recipient unit. Other evidence, though, suggests that recipients need to adapt the practice to fit their local environment. The current research introduces a contingency perspective on practice transfer, holding that the value of modifications depends on when they are introduced and who introduces them. Empirical research on the transfer of a quality-improvement practice between projects within Wikipedia shows that modifications are more helpful if they are introduced after the receiving project has had experience with the imported practice.
Furthermore, modifications are more effective if they are introduced by members who have experience in a variety of other projects. Few studies have investigated how to manage these conflicts effectively. Yuan Yao and Svetlana E. Nowadays, more people in recovery choose to seek help from online support groups. This paper presents Group Finder, a content-based online support groups recommender that makes suggestions by using the measurements of post contents in social and psychological dimensions.
Thanh-Mai Phan and Svetlana E. The concept of reciprocity is embedded into community. A successful online peer-support community is characterized by its members actively giving and receiving support, namely in the form of advice and encouragement. In this paper, we investigate incentives for sustaining generalized reciprocity and explore its relationship with social capital on InTheRooms.
Jialun Jiang and Svetlana E. Why Do Teammates Hate Me? We discuss the multi-ethnic tension and social dynamics behind toxicity in online game Dota 2. We present a player survey and preliminary analysis of user-generated keywords and future work in interpreting the survey results. Timothy Pallarino, Aaron E. Free, Katrina Mutuc, and Svetlana Yarosh. Physical distance presents a challenge for building and maintaining relationships.
With recent work showing the effectiveness of both visual and haptic feedback in supporting interpersonal touch over a distance, such technologies look to bridge this gap and improve existing communication technologies. In this project, we explore the potential role of shape-shifting displays for doing so. We present two prototypes, one using linear slide potentiometers and the other using linear actuators, that incorporate these forms of feedback to facilitate mediated social touch. We present the benefits and drawbacks of each system, and conclude that, for a system focused on collaboration and synchronous communication, linear actuators may be better suited due to their load capacity and precision.
Does the Sharing Economy do any Good?
Despite the benefits offered by sharing economy, researchers have identified several challenges preventing disadvantaged groups e. This panel brings researchers from the sharing economy and mobile crowdsourcing space whose research has identified unique challenges for underserved populations.
We consider the opportunities offered by these platforms to disadvantaged communities and examine to what extent these platforms instead may recreate disadvantage, as well as the workarounds communities employ to make these platforms work for them. We examine the opportunities for the CSCW community to address these challenges going forward.
Online communities suffer serious newcomer attrition. We find that DSCORE is significant both by itself and in conjunction with a measure of quantity of activity in predicting longevity. This finding is robust to different measures of longevity aggregate number of sessions and attritions after sessions 1, 5, and The immediate implication is an effective classifier for identifying users with higher or lower expected longevity from the first-session activity.
We conclude by discussing how early activity diversity may be more broadly effective in supporting design and management of online communities. HCI without borders? Maxwell Harper and Joseph A. ACM Trans. The MovieLens datasets are widely used in education, research, and industry. They are downloaded hundreds of thousands of times each year, reflecting their use in popular press programming books, traditional and online courses, and software.
These datasets are a product of member activity in the MovieLens movie recommendation system, an active research platform that has hosted many experiments since its launch in This article documents the history of MovieLens and the MovieLens datasets. We include a discussion of lessons learned from running a long-standing, live research platform from the perspective of a research organization.
We document best practices and limitations of using the MovieLens datasets in new research. Joseph A. Konstan and Jack W. Should Conferences Meet Journals and Where? ACM 58, 9: 5—5. Charting the future: scholarly publishing in CS.
Communications of the ACM 58, 4: 5—5. Jeremy A. Michael Wilkerson, Dylan Galos, and B.
Presidential Tax Returns
Simon Rosser. AIDS and Behavior 19, — Researchers use protocols to screen for suspicious survey submissions in online studies. We evaluated how well a de-duplication and cross-validation process detected invalid entries. Using our protocol, We found few demographic or behavioral differences between valid and invalid samples, however.
Thus, rates of HIV testing would have been underestimated if invalid submissions had not been removed, and payment may not be the only incentive for invalid participation. Isaac Johnson and Brent Hecht. A critical subset of human-generated content is that which is geographically referenced. The spatial context of these data has enabled a new class of observational studies and tech-nologies.
Unfortunately, researchers have identified a num-ber of biases in these datasets e. However, these findings have been highly spe-cialized, focusing on single datasets and dimensions of bias. This extended abstract seeks to begin the process of synthe-sizing a cohesive understanding of the structural causes of bias in geographically-referenced human content. We out-line five cross-cutting causational factors, as well as intro-duce a novel framework that aids in understanding these factors. In doing so, we hope to initiate a discussion that moves the literature on bias in geographic content towards one focused on systemic issues.
This would allow the antic-ipation of bias in unseen datasets and, importantly, enable research towards systemic solutions. Maxwell Harper, and Loren Terveen. To achieve high quality initial personalization, recommender systems must provide an efficient and effective process for new users to express their preferences. We propose that this goal is best served not by the classical method where users begin by expressing preferences for individual items - this process is an inefficient way to convert a user's effort into improved personalization.
Rather, we propose that new users can begin by expressing their preferences for groups of items. We test this idea by designing and evaluating an interactive process where users express preferences across groups of items that are automatically generated by clustering algorithms. We contribute a strategy for recommending items based on these preferences that is generalizable to any collaborative filtering-based system. We evaluate our process with both offline simulation methods and an online user experiment. We find that, as compared with a baseline rateitems interface, a users are able to complete the preference elicitation process in less than half the time, and b users are more satisfied with the resulting recommended items.
Our evaluation reveals several advantages and other trade-offs involved in moving from item-based preference elicitation to group-based preference elicitation. Ekstrand, Daniel Kluver, F. Recommender systems are not one-size-fits-all; different algorithms and data sources have different strengths, making them a better or worse fit for different users and use cases. As one way of taking advantage of the relative merits of different algorithms, we gave users the ability to change the algorithm providing their movie recommendations and studied how they make use of this power.
We conducted our study with the launch of a new version of the MovieLens movie recommender that supports multiple recommender algorithms and allows users to choose the algorithm they want to provide their recommendations. We examine log data from user interactions with this new feature to under-stand whether and how users switch among recommender algorithms, and select a final algorithm to use. We also look at the properties of the algorithms as they were experienced by users and examine their relationships to user behavior.
The majority of users who used the control only switched algorithms a few times, trying a few out and settling down on an algorithm that they would leave alone. The largest number of users prefer a matrix factorization algorithm, followed closely by item-item collaborative filtering; users selected both of these algorithms much more often than they chose a non-personalized mean recommender.
The algorithms did produce measurably different recommender lists for the users in the study, but these differences were not directly predictive of user choice. Putting Users in Control of Their Recommendations. The essence of a recommender system is that it can recommend items personalized to the preferences of an individual user.
But typically users are given no explicit control over this personalization, and are instead left guessing about how their actions affect the resulting recommendations. We hypothesize that any recommender algorithm will better fit some users' expectations than others, leaving opportunities for improvement. To address this challenge, we study a recommender that puts some control in the hands of users. Specifically, we build and evaluate a system that incorporates user-tuned popularity and recency modifiers, allowing users to express concepts like "show more popular items".
We find that users who are given these controls evaluate the resulting recommendations much more positively. Further, we find that users diverge in their preferred settings, confirming the importance of giving control to users. Konstan, and Paul Schrater. Studies have shown that the recommendation of unseen, novel or serendipitous items is crucial for a satisfying and engaging user experience.
As a result, recent developments in recommendation research have increasingly focused towards introducing novelty in user recommendation lists. While, existing solutions aim to find the right balance between the similarity and novelty of the recommended items, they largely ignore the user needs for novelty.
In this paper, we show that there are large individual and temporal differences in the users' novelty preferences. We develop a regression model to predict these dynamic novelty preferences of users using features derived from their past interactions. Towards domain-specific semantic relatedness: a case study from geography. Semantic relatedness SR measures form the algorithmic foundation of intelligent technologies in domains ranging from artificial intelligence to human-computer interaction.
Although SR has been researched for decades, this work has focused on developing general SR measures rooted in graph and text mining algorithms that perform reasonably well for many different types of concepts. This paper introduces domain-specific SR, which augments general SR by identifying, capturing, and synthesizing domain-specific relationships between concepts. Using the domain of geography as a case study, we show that domain-specific SR -- and even geography-specific signals alone e.
In addition to substantially improving SR measures for geospatial technologies, an area that is rapidly increasing in importance, this work also unlocks an important new direction for SR research: SR measures that incorporate domain-specific customizations to increase accuracy. By examining five years' archival data of Stack Overflow, we found that the benefits of collaborative editing outweigh its risks. This work has implications for understanding and designing large-scale social computing systems.
Shilad W. Sen, Heather Ford, David R. Musicant, Mark Graham, Oliver S. Keyes, and Brent Hecht. Barriers to the Localness of Volunteered Geographic Information. Localness is an oft-cited benefit of volunteered geographic information VGI. This study examines whether localness is a constant, universally shared benefit of VGI, or one that varies depending on the context in which it is produced.
Focusing on articles about geographic entities e. We find extensive geographic inequalities in localness, with the degree of localness varying with the socioeconomic status of the local population and the health of the local media. We also point out the key role of language, showing that information in languages not native to a place tends to be produced and sourced by non-locals.
Willingly Published: More Papers to 2005
We discuss the implications of this work for our understanding of the nature of VGI and highlight a generalizable technical contribution: an algorithm that determines the home country of the original publisher of online content. Recent work has identified the lack of space usage rule SUR data -- e. In order to address this limitation, a large-scale means of mapping SURs must be developed. In this paper, we introduce and motivate the problem of mapping space usage rules and take the first steps towards identifying solutions.
Its focus was on self-archiving. Self-archiving activity is greatest amongst those who publish the largest number of papers. There is still a substantial proportion of authors unaware of the possibility of providing open access to their work by self-archiving. Where it is not known if permission is required, however, authors are not seeking it and are self-archiving without it. Communicating their results to peers remains the primary reason for scholars publishing their work; in other words, researchers publish to have an impact on their field.
How many subscriptions have been lost as a result of arXiv? Both societies said they could not identify any losses of subscriptions for this reason and that they do not view arXiv as a threat to their business rather the opposite -- this in fact the APS helped establish an arXiv mirror site at the Brookhaven National Laboratory. Downloads from ePrints over the past year.
Other digital versions may also be available to download e. The choice of a publication outlet can be seen as a submission tree. The submission tree model implies that authors aim for the top journals in the first submission and, if the article is rejected, follow the path established and submit to a second or a third journal e. Heintzelman and Nocetti , p. Oster suggests the following four characteristics of a journal to include: prestige index, familiarity index, mean waiting time, and acceptance probability.
Other frameworks exist, but there are great overlaps in the categorization e. Open access is not a factor that determines the publishing strategies of researchers in general, although there are differences across, for example, fields and means of funding Tenopir et al. A survey by Rowlands and Nicholas indicates that the most important criteria for selecting a journal to publish in are in descending order of importance : the reputation of the journal, readership, impact factor, speed of publication, and reputation of editorial board.
Prestige, readership, and topic frequency are the most important criteria in the study by Frank Soreide and Winter do not include audience or readership, and thus, other factors are found to be more important, that is, impact factor, overall reputation, and fast track. Summing up, the existing literature on how authors decide on a publication outlet includes author characteristics, journal characteristics, and other research characteristics as factors.
Few studies exist on the awareness and motivation of authors who publish their work in questionable journals, and it is difficult to ask the authors of such publications as they will probably claim unawareness or defend the journal regardless. In a recent case of 5, German researchers found to be authors of articles in questionable journals, not one has come forward to admit to being aware that the chosen journal probably did not adhere to acceptable academic standards.
In other cases, authors of articles in deceptive journals are found to be the greatest defenders of the journals Beall, Empirical approaches to the question include a study by Kurt that identifies four themes on the basis of a survey study using a grounded theory and qualitative methods approach for data collection and analysis: Social identity threat Unawareness High pressure Lack of research proficiency.
Social identity threat is the fear of being viewed as inferior to others because of belonging to a particular group, which is the case for some researchers from developing countries or researchers with poor English abilities. Not being aware that the journal was predatory was another factor that leads to different levels of concerns. Some might even publish in them again. Publishing may be tied to a position leading to high pressure to publish. However, the methods used in the survey may have bearing on the results. The empirical work by Kurt is based on a survey dealing with a number of sensitive questions.
Furthermore, a strong pressure to publish is mentioned in the survey as an explanation for choosing the specific journal, and thus, an explanation is offered to the respondents. Consequently, although empirically based, Kurt probably only offers a part of the explanation.
They find that acceptance likelihood is the main reason for the choice of a deceptive journal. Based on 30 interviews with Nigerian researchers, Omobowale, Akanle, Adeniran, and Adegboyega find four explanations for authors choosing a deceptive publication outlet: Colleagues using the journals and achieving promotion Achieving rapid promotion Ignorance Inadequate evaluations. Researchers see their colleagues achieve promotion on the basis of deceptive publication outlets and thus becoming zombie professors, which can lead them to follow their path.
They may be able to publish in decent journals but use the deceptive journals to fast track their promotion. Third, researchers may be ignorant of the quality of the deceptive journals. Finally, articles in questionable journals are accepted without adequate scrutiny by appointment and promotion committees. Omobowale et al. Summing up, the explanations for publishing in a deceptive or deceptive journal include lack of awareness and different perspectives on motivation as well.
Explaining why authors publish in deceptive journals may thus consist of a combination of awareness and motivation. In understanding why authors publish in a deceptive journal, we can draw on the literature on questionable research behaviour and scientific misconduct. Publishing in a deceptive journal can be considered questionable research conduct. Ideal research behaviour can be characterized as responsible conduct of research, whereas research behaviours that fall short of responsible conduct can be termed deliberate misconduct and questionable research practices Steneck, In the existing literature addressing deceptive journals, we have, so far, focused primarily on what Grimes et al.
They fall prey as they are not aware that the journal they have published in is in fact deceptive. Moher et al.