User Contributions Research Articles

Consequences of Information Feed Integration on User Engagement and Contribution: A Natural Experiment in an Online Knowledge-Sharing Community

This paper investigates the ramifications of information feed integration on user engagements and contributions in online content-sharing platforms by exploiting a natural experiment occurred in a leading knowledge-sharing platform that integrated informal social posts with professional knowledge content in one feed. Our results show that the juxtaposition of incongruous types of content increased mindset switching and cognitive strain, thus hurting user engagements. We also reveal a novel crowding-out effect, viz., the integration heightened concerns that posting informal social posts would dilute the contributor’s professional image, thus inhibiting user contributions. Our findings hold important practical implications for all platforms that host (or are considering hosting) diverse types of user-generated content (UGC). Additional content curation tools can potentially enhance user engagement and retention, but their effectiveness hinges on a foundational and crucial element—the presentation format of heterogeneous content types. Essentially, the value of curating informal social posts in a knowledge-sharing platform would diminish when those content intrudes upon and conflict with the professional domain. This insight underscores that any UGC platforms, when adopting a diversity-oriented strategy, should pay close attention to heterogeneity between different content types for the purpose of optimizing user experiences and promoting user contributions.

Exploring Discursive Strategies of Dark Participation: User Comments on Migration in New York Times and Τhe Guardian

ABSTRACT Digital media have multiplied the range of voices circulating in the public sphere(s), a terrain where journalists enjoyed special communication power. Despite optimism, research has offered mixed findings regarding the outcomes of participatory journalism assuming both constructive and negative interactions. This article draws from, and contributes, to a more nuanced exploration of “dark participation”, a concept broadly used to conceptualise online user contributions that are evil, tactical or strategic. Specifically, the article focuses on user comments in New York Times and the Guardian during the so-called 2015 “refugee crisis”. In addressing descriptive and exploratory research questions, it illustrates how dark participation can include disguised but equally strategic discursive strategies, like disclaimers and “half-truths” which may not always transgress the norms of civility but still tend to manipulate the conversation and normalise stereotyping and exclusion. Moreover, the study provides evidence associating antimigrant discourse with media attacks invoking radical right-wing populist narratives of “leftist” and “hypocritic” media operating as propaganda machines aiming to undermine the media’s integrity and neutralise their editorial position. The (intended) proliferation of antimigrant views and discourses associated with media attacks can be considered as a strategy to discourage inclusive and critical media reporting.

Recognition of opinion leaders in blockchain-based social networks by structural information and content contribution.

Exploring the influence of social network users in the blockchain environment and identifying opinion leaders can help understand the information dissemination characteristics of blockchain social networks, direct the discovery of quality content, and avoid the spread of rumors. Members of blockchain-based social networks are given new responsibilities by token awards and consensus voting, which alters how users connect to the network and engage with one another. Based on blockchain theory and the relevant theories of opinion leaders in social networks, this article combines structural information and content contributions to identify opinion leaders. Firstly, user influence indicators are defined from the perspective of network structure and behavioral characteristics of user contributions. Then, ECWM is constructed, which combines the entropy weight method and the criteria importance through intercriteria correlation (CRITIC) weighting method to address the correlation and diversity among indicators. Furthermore, an improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), called ECWM-TOPSIS, is proposed to identify opinion leaders in blockchain social networks. Moreover, to verify the effectiveness of the method, we conducted a comparative analysis of the proposed algorithm on the blockchain social platform Steemit by using two different methods (voting score and forwarding rate). The results show that ECWM-TOPSIS produces significantly higher performance than other methods for all selected top N opinion leaders.

Community Activation for Disaster Risk Reduction Through OpenStreetMap: A Scoping Review

The advancement of geospatial technology has significantly altered how data is utilised for facilitating the growth of open-access data for disaster risk reduction (DRR). OpenStreetMap (OSM) is a part of Volunteered Geographic Information (VGI), built on the concept of volunteerism and heavily reliant on user contributions to spatial data. In recent years, OSM has emerged as a fundamental tool in all aspects of DRR, enabling well-informed decision-making and empowering active community contributions. This study aims to review the utilisation of OSM in DRR and proposes recommendations to enhance community resilience. The five-step scoping review method was conducted on 25 selected papers to investigate the current knowledge and uncover the potential applications of OSM within the community for DRR. The review commenced by defining the research questions, identifying pertinent literature sources, selecting relevant literature for inclusion, extracting key themes from the literature, and finally, consolidating, summarising, and reporting the results. The findings revealed that OSM’s worldwide accessibility for various objectives has been instrumental in its widespread adoption and rising prominence. Nevertheless, this review emphasises that despite its rapid expansion into other fields, OSM continues to hold significant importance and widespread usage in the context of DRR. This study presented findings on community involvement in OSM and explored the opportunities for community-led DRR implementation. The paper provides insights into the application of OSM in advanced and developing countries while delving into potential future pathways. OSM places significant emphasis on community-driven, on-the-ground data collection, providing governments with a chance to enhance policy management in DRR. As the incorporation of OSM in decision-making expands, it will garner attention from diverse sectors, demonstrating the platform’s effectiveness on a broader and more impactful level.

Virtues and shortcomings of guidance and tutoring in higher education: a longitudinal study of the TIMONEL Project

This research is established within the framework of Project TIMONEL, developing in three phases under a concurrent mixed research model. The ultimate goal was to create a Web Recommendation System (RS) to complete the tutorial and guidance work of university professors. Both qualitative and quantitative data are collected from a large sample of students and professors from different European universities on the needs and situation of guidance practice (phase 1). In addition, certain cases are investigated and the reasons, knowledge, feelings and good practices in guidance and tutoring are explored, in order to identify opportunities for improvement and elements that enable the design of the RS (phase 2). The data collected in the first and second phases of project development were used to finally build a SR capable of receiving feedback from user contributions (phase 3). Finally, the SR was evaluated, proving to be a tool of great use for university students and faculty.

Institutional pathways for transforming groundwater planning and management: Reflections from Pakistan and Sri Lanka

AbstractThe growing issues with groundwater quality and quantity worldwide are particularly impacting regions of South Asia, where groundwater use plays a crucial role in human well‐being. As the severity of the situation becomes clearer, there are increasing calls for transformation in water management. In this paper, we consider institutional influences on transforming groundwater management by reflecting on our recent collaborative research in Pakistan and a scoping study in Sri Lanka. In Pakistan, we have shown that it is possible for previously “siloed” stakeholders to develop shared understandings of the groundwater situation and build useful and enduring practice networks. Such shared understandings can support collaborative planning, but must be informed by effective monitoring and modeling, and an institutional willingness to think beyond traditional formal regulatory tools. Regional and local scale planning could encourage interactive processes for broader thinking. Given the similarity in the human‐groundwater situation between parts of Pakistan and Northern Sri Lanka, we undertook a small study to see if similar collaborative research would be valuable there. Our brief visit confirmed commonalities in the situation. By reflecting on our experience in Pakistan and Sri Lanka, we make a case for encouraging and embracing collaborative research as part of transforming water resources management. Our approach emphasizes the important contributions of both water managers and users and encourages ways of integrating paradigms, knowledge, norms, and practices. Establishing genuine co‐inquiry among groundwater managers and users requires a deeper appreciation of the constraining and enabling roles established institutions can play and thus ultimately a transformation in institutional arrangements.

Community Blogs Implementation for an Organization

Abstract: Community-based blogging sites can be excellent resources for knowledge on a wide range of specialized subjects. Such systems' usefulness significantly depends on user participation and contribution. In addition to offering information and resources on specialized subjects. These websites can promote a sense of belonging and support, and they can be a great place to gather advice and information on particular subjects.

A Research on User Contributions in Healthcare Financing

Bu çalışma, araştırmanın yürütüldüğü tarih itibariyle son bir yıl içerisinde sağlık kurumlarından sağlık hizmeti almış kişilerin kullanıcı katkılarına ilişkin bilgi düzeyleri ve görüşlerinin belirlenmesi amacıyla yapılmıştır. Araştırmada veri toplama yöntemi olarak anket kullanılmıştır. Çalışmada amaçlı örnekleme yöntemi yoluyla toplam 670 kişiye ulaşılmıştır. Çalışmada analiz yöntemi olarak tanımlayıcı istatistik yöntemleri ve Ki-kare analizi kullanılmıştır. Araştırmada katılımcıların %15,4’ü uygulanmakta olan kullanıcı katkı miktarları hakkında bilgi sahibi olduğunu ifade ederken, %84,6’sı kullanıcı katkıları hakkında herhangi bir bilgilerinin olmadığını belirtmişlerdir. Katılımcıların %70,1’i eczaneye ödemiş oldukları kullanıcı katkısının belirli bir bölümünün sağlık kurumlarından almış oldukları hizmetin bedeli olduğunu bilmektedir. Katılımcıların %15,2’si kullanıcı katkısı alınmayacak haller, sağlık hizmetleri ve kişiler hakkında bilgilerinin olduğunu belirtmişlerdir. Bu bulgular sonucunda kullanıcı katkılarının daha etkili ve verimli uygulanabilmesi için kullanıcı katkılarına yönelik kişilerin bilgi düzeyini artırıcı çalışmalar yapılması gerektiği söylenebilir. Bu kapsamda sağlık hizmeti kullanıcılarında bilinç düzeyinin artması için ilgili kurumlar tarafından konuyu açık bir şekilde anlatan broşürler dağıtılabilir ve özellikle kullanıcı katkılarını anlatan kamu spotları yayınlanabilir.

Participation shaping the values of news articles: implications of news as anti-rival information products

ABSTRACTIn the literature, anti-rivalry has been proposed to describe goods that become more valuable when used. Empirical testing of this theory is lacking, and the concept has not yet been applied in the context of news. This study identifies five distinctive value constructs – news value, emotional value, value of reading comments, social value of commenting and social value of sharing – from the statistical analysis of a survey of 2020 online news consumers on Finnish public broadcaster Yle’s website. We then assess changes in these values when the news is consumed and users have contributed to it by commenting on it and sharing it. The results of the analysis and additional in-depth user interviews indicate that news possesses elements of anti-rivalry. Additionally, the results indicate interesting intercorrelations among the values and user groups. When a piece of news has high news value, user contributions do not play a major role, but the value of sharing increases. When a news product is commented on, the act increases the social value of sharing for sharers, decreases the news value for readers and increases the negative emotions felt by readers.

Token Incentives in a Volatile Crypto Market: The Effects of Token Price Volatility on User Contribution

ABSTRACT Crypto tokens, issued and managed via smart contracts, function as rewards in blockchain systems to encourage user participation. Distinct from monetary incentives, token incentives are uncertain in reward magnitude due to the large swings in token prices on crypto markets. By focusing on token price volatility, this study investigates how the reward uncertainty affects user contribution in a tokenized digital platform. Our empirical setting is Steemit, a platform where bloggers write posts and share token rewards based on their posts’ popularity. We find that while high token price volatility induces a large volume of blog posts, it diminishes post quality. The dichotomous effects are explained via two mechanisms: users’ direct reactions to reward uncertainties and their indirect reactions, mediated by altered token preference amid volatility shocks. Deeply exploring this dynamic process, our results reveal that token price volatility facilitates a platform’s network short-term effect but impairs long-term user creativity. Our empirical findings thus extend the literature on blockchain economics and cryptocurrencies and have practical implications for the design of incentive mechanisms on tokenized digital platforms.

Are sticky users less likely to lurk? Evidence from online reviews

ABSTRACT Although many product providers deem user contributions (e.g. online reviews) important, providers often struggle to obtain them, i.e. most users are lurkers who are reluctant to post reviews. This study is conducted to understand better how to delurk users by investigating the role of user stickiness in review posting behaviour. By employing a large-scale dataset from TapTap, a Chinese mobile game community, and conducting a multimethod investigation, this study found that sticky users with a product are more likely to engage in review posting behaviour related to the product. Also, this positive stickiness-post effect varies for some user and product features: (a) the positive relationship between user stickiness and posting behaviour will be strengthened as user expertise rises, (b) the positive stickiness-post relationship will be alleviated when products are collaborative-consuming products (vs. private-consuming products), (c) and the positive stickiness effect on review posting behaviour will be stronger when product providers are small-scale (vs. large-scale). These findings provide a comprehensive understanding of biases in lurking/posting behaviour related to user stickiness and help product providers gain insights into delurking users and gathering user intelligence.

A temporal graph framework for intelligence extraction in social media networks

Social media networks (SMNs) are increasingly used in professional management of knowledge workers and related assets. However, the factors affecting behavioral trends and activity levels in these networks are not well understood. Although social and cognitive theories can help to explain human behavior in traditional social networks, their application to SMNs has not been validated. Traditional social network modeling techniques may not accurately predict real-world SMN activities. This research developed a temporal graph framework for intelligence extraction in SMNs. Theory-based, data-driven models (Conformity Model (COM), Recency-Primacy Model (REM), Trend Interaction Model (TIM), Periodic Interaction Model (PIM)) were developed based on the framework to capture various aspects of user behavior: conformity effect, recency, primacy, periodicity, and dynamic trend. The models capture the activity history and dynamically combine pricing information to enhance predictive accuracy. Using data of 83,536 GitHub software repositories on cryptocurrency, this article reports the results of experiments that compare the models’ performance in predicting SMN activities over time. Experimental results show that the model (REM) that captures recency/primacy effects of human cognitive processing outperformed other models in 9 (out of 18) measures pertaining to engagement, contribution, influence, and popularity. Primacy plays a dominant role in predicting engagement, contribution, and popularity, whereas recency plays a key role in predicting influence. Short-term trend (modeled with TIM) was found to yield significantly better performance on predicting user contribution. The models also outperformed an integrated machine learning (IML) model by most measures. Overall, the effects modeled by REM and TIM were found to be more significant than the effects modeled by COM, PIM, and IML. The research contributes to enhancing understanding of SMN behavior, developing new models to simulate and predict SMN activities, and designing new artifacts for information systems practitioners to manage knowledge assets and to extract SMN intelligence.

Research on the formation mechanism of product contribution in online product communities: content contribution as a mediating variable

PurposeEnterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous literature rarely focused on both. The purpose of this paper is to explain user contribution mechanism by identifying content contribution and product contribution.Design/methodology/approachThis research chose Xiaomi-hosted online product community (bbs.xiaomi.cn) and Huawei-hosted online product community (club.huawei.com) where users can freely share ideas and buy products at the same time. Data were crawled from 109,665 community users to construct dependent variable measurement, and 611 questionnaires were used to verify research hypotheses.FindingsThe results indicate that both cognitive needs and personal integration needs have a significant positive impact on browse behavior; social integration needs and hedonic needs have a significant positive impact on content contribution behavior. Browse behavior not only directly affects but also indirectly influences product contribution through content contribution behavior.Research limitations/implicationsFindings of this research provide community managers with useful insights into the relationship between content contribution and product contribution.Originality/valueThis study explains the formation mechanism of user product contribution and reveals the relationship between user content contribution and product contribution in online product community. This paper provides a different way of theorizing user contributions by incorporating uses and gratifications theory into the “Motivation-Behavior-Result” framework.

Invoking and identifying task-oriented interlocutor confusion in human-robot interaction.

Successful conversational interaction with a social robot requires not only an assessment of a user's contribution to an interaction, but also awareness of their emotional and attitudinal states as the interaction unfolds. To this end, our research aims to systematically trigger, but then interpret human behaviors to track different states of potential user confusion in interaction so that systems can be primed to adjust their policies in light of users entering confusion states. In this paper, we present a detailed human-robot interaction study to prompt, investigate, and eventually detect confusion states in users. The study itself employs a Wizard-of-Oz (WoZ) style design with a Pepper robot to prompt confusion states for task-oriented dialogues in a well-defined manner. The data collected from 81 participants includes audio and visual data, from both the robot's perspective and the environment, as well as participant survey data. From these data, we evaluated the correlations of induced confusion conditions with multimodal data, including eye gaze estimation, head pose estimation, facial emotion detection, silence duration time, and user speech analysis-including emotion and pitch analysis. Analysis shows significant differences of participants' behaviors in states of confusion based on these signals, as well as a strong correlation between confusion conditions and participants own self-reported confusion scores. The paper establishes strong correlations between confusion levels and these observable features, and lays the ground or a more complete social and affect oriented strategy for task-oriented human-robot interaction. The contributions of this paper include the methodology applied, dataset, and our systematic analysis.

Research on adjustable load dividend transmission strategy under aggregate operation mode

In recent years, the scale of inter-provincial and inter-regional power transmission keeps growing, the proportion of new energy keeps rising, and the complexity of power grid structure increases the risk of its operation control. Under the aggregation operation mode, the adjustable load has great electricity elasticity. Guiding its electricity consumption behavior and making it participate in the power grid regulation operation can greatly improve the safety of operation, promote the absorption of new energy and realize the optimal allocation of power resources. This paper studies the form of adjustable load participation in grid regulation in different scenarios under the aggregate operation mode, analyzes the cost and benefit of adjustable load participation in electricity market transactions, and then combines the evaluation method based on the contribution of adjustable load users in different scenarios to propose a dividend transmission strategy of adjustable load in the aggregate operation mode.

Towards mobility reports with user-level privacy

ABSTRACT The importance of human mobility analyses is growing in both research and practice, especially as applications for urban planning and mobility rely on them. Aggregate statistics and visualizations play an essential role as building blocks of data explorations and summary reports, the latter being increasingly released to third parties such as municipal administrations or in the context of citizen participation. However, such explorations already pose a threat to privacy as they reveal potentially sensitive location information, and thus should not be shared without further privacy measures. There is a substantial gap between state-of-the-art research on privacy methods and their utilization in practice. We thus conceptualize a mobility report with differential privacy guarantees and implement it as open-source software to enable a privacy-preserving exploration of key aspects of mobility data in an easily accessible way. Moreover, we evaluate the benefits of limiting user contributions using three data sets relevant to research and practice. Our results show that even a strong limit on user contribution alters the original geospatial distribution only within a comparatively small range, while significantly reducing the error introduced by adding noise to achieve privacy guarantees.

The value allocation model of renewable portfolio standards considering the contribution of renewable energy consumption on the demand side

Under China's current Renewable Portfolio Standards (RPS) policy system, the provincial power grid is the assessment subject, and then the assessment is conducted on the user side. However, in the centralized clearing power market, renewable energy (RE) consumption on the user side cannot be accurately identified, so accurate value transmission cannot be formed to guide users to optimize their electricity consumption behavior. To improve this problem, this paper identifies the irreplaceable role of users in RE consumption through time series simulation. We construct a three-layer RPS assessment value transmission model of “power grid company - retailers - users” based on the identified unique contributions of each user. The equilibrium state of multi-market participants is obtained based on the decentralized training framework of reinforcement learning. The following conclusions are drawn through simulation analysis:(1) the user-side RE contribution identification method can effectively identify the user's contribution to RE consumption, which can reduce about 8% or increase about 7.48% of RPS cost allocation according to different contribution degrees; (2) the RPS value allocation mode can optimize users' power consumption behavior, achieve peak shaving and valley filling, promote RE consumption, and reduce about 0.6% of the abandoned wind power; (3) Under the RPS system, the effect of improving the response-ability of the user-side is better than increasing the RPS target and the peak shaving capacity.

What Do Users Think of Promotional Gamification Schemes? A Qualitative Case Study in a Question Answering Website

In recent years, studies on the user experience have emerged as an indispensable part of any gamification research. The study of user experience enables gamification designers and practitioners to design or adapt their gamification schemes in a more knowledgeable and efficacious manner. However, one popular gamification scheme that has largely remained under-researched in terms of user experience is promotional gamification, which refers to an optional and time-limited gamification program that usually mounts an already gamified platform to increase user incentive and engagement for a short span of time (e.g., during the holiday season). The current study undertakes the first steps necessary to explore users' experiences of working with a promotional gamification scheme in a large-scale online community. To this end, we conduct an extensive qualitative case study of users' experiences with a promotional gamification scheme on the Community Question Answering Website (CQA) of Stack Exchange, called Winter Bash (WB). Notably, the purpose of WB is to operate as a makeshift solution that prevents the decline in user contributions during the holiday season. However, like many other gamification schemes, WB is not devoid of issues, and our research helps identify those issues without overlooking the WB's strengths. Our study denotes not only the first (empirical) typology of users' affective responses to promotional gamification schemes but also the first classification of (de)motivational factors involved in user engagement. At its core, this study comprises two salient parts: (1) a content analysis of user-generated data regarding WB (from the past eight years), and (2) a series of semi-structured interviews with 17 international users who are familiar with WB. We triangulate our findings from (1) and (2) by performing a similar content analysis for two other promotional gamification schemes, namely "Answerathon" (from Travel Meta) and "Discussion Tournament" (from Reddit). Based on the findings of this study, we present certain guidelines for gamification designers and practitioners, enabling them to deploy or adapt their promotional gamification schemes in a more knowledgeable and effective manner. Finally, our work is concluded by highlighting a few novel research opportunities for researchers invested in the fields of Human-Computer Interaction (HCI) and Computer-Supported Cooperative Work (CSCW).

More Gamification Is Not Always Better

Community Question Answering Websites (CQAs) like Stack Overflow rely on continuous user contributions to keep their services active. Nevertheless, they often undergo a sharp decline in their user participation during the holiday season, undermining their performance. To address this issue, some CQAs have developed their own special promotional gamification schemes to incentivize users to maintain their contributions throughout the holiday season. These promotional gamification schemes are often time-limited, optional, and run alongside the default gamification schemes of their websites. However, the impact of such promotional gamification schemes on user behavior remains largely unexplored in the existing literature. This paper takes the first steps toward filling this knowledge gap by conducting a large-scale empirical study of a particular promotional gamification scheme called Winter Bash (WB) on the CQA of Stack Overflow. According to our findings, promotional gamification schemes may not be the panacea they are portrayed to be. For example, in the case of WB, we find that the scheme is not effective for improving the collective engagement of all users. Only some particular user types (i.e., experienced and reputable users) are often provoked under WB. Most novice users, who comprise the majority of Stack Overflow website's user base, seem to be indifferent to such a gamification scheme. Our research also shows the importance of studying the quantity and quality of user engagement in unison to better understand the effectiveness of a gamification scheme. Previous gamification studies in the literature have focused predominantly on studying the quantity of user engagement alone. Last but not least, we conclude our paper by presenting some practical considerations for improving the design of future promotional gamification schemes in CQAs and similar platforms.

Administrator-users contribute more to online communities

Lack of user participation and contribution has been a long-standing problem for online communities. We proposed and examined new strategies for cultivating opinion leadership and enabling users to post articles outside of the community theme. We used social role theory to propose that online communities should encourage highly committed users to take administrator roles, which will increase their opinion leadership and contributions to both public spaces and their own user-controlled spaces. We collected multiple-wave and multiple-source data from 1,115 users of a large online community. The results indicate that encouraging users to take administrator roles increases their community contributions.