Online Users Research Articles

(Im)politeness as a Strategy in the Discursive Construction of In-Group Solidarity in Discussions about Love, Sex and Relationships on Incels.is

As a discourse community that is formed and maintained mostly online, involuntary celibates (who are typically heterosexual men) have been known to be one of the most obvious groups presenting misogynistic attitudes (Bates 2020). There are various forums where such online users meet to discuss subjects of relevance to them, including Reddit and subreddit threads (r/incels) and websites specifically targeted at the community (such as Incels.is). Although the subject of incel discourses has been addressed from several linguistic perspectives, including the representation of social actors (Heritage & Koller 2020), toxic language in the community (Pelzer et al. 2021), metaphor (Heritage et al. 2023) and the extreme language of misogyny (Bogetić 2022), still relatively little has been written specifically about how the community of practice is formed on the basis of the discursive expression of solidarity. The present paper is an analysis of discussions on the forum Incels.is on the subject of sex and relationships, specifically investigating how both manifestations of misogynist attitudes and discursive strategies of politeness are used to form solidarity between users. The analysis considers that through the employment of positive and negative politeness strategies in an online community, group bonds are made stronger and in-group solidarity is expressed both directly and indirectly. The analysis of politeness strategies showed that positive politeness and negative politeness were both present as face-saving acts and to construct solidarity through the use of sarcasm, kinship claiming, informal language and the negative evaluation of female actors.

Patterns matter? A cross-sectional study on social and usage patterns of smartphone internet service and self-perceived addiction in Taiwan

ABSTRACT The purpose of this cross-sectional study is to examine the level of smartphone online usage patterns and self-perceived addiction in Taiwan. In this study, we argued that differential frequency of online usage patterns gave rise to significant differences between two groups of users in terms of their perception of smartphone addiction. Based on a sample of 1,012 smartphone users aged 12 or above in the nationwide survey of Taiwan’s National Development Council in 2018, we examined the relations between background characteristics, internet-related factors and 10 types of smartphone online usage patterns. The results of multiple logistic regression indicated that social media use can predict the self-perception of smartphone online addiction. Differences between participants of different education levels, age groups and gender in binary smartphone addiction variables were also revealed.

Investigating Characteristics of Media Recommendation Solicitation in r/ifyoulikeblank

Despite the existence of search-based recommender systems like Google, Netflix, and Spotify, online users sometimes may turn to crowdsourced recommendations in places like the r/ifyoulikeblank subreddit. In this exploratory study, we probe why users go to r/ifyoulikeblank, how they look for recommendation, and how the subreddit users respond to recommendation requests. To answer, we collected sample posts from r/ifyoulikeblank and analyzed them using a qualitative approach. Our analysis reveals that users come to this subreddit for various reasons, such as exhausting popular search systems, not knowing what or how to search for an item, and thinking crowd have better knowledge than search systems. Examining users query and their description, we found novel information users provide during recommendation seeking using r/ifyoulikeblank. For example, sometimes they ask for artifacts recommendation based on the tools used to create them. Or, sometimes indicating a recommendation seeker's time constraints can help better suit recommendations to their needs. Finally, recommendation responses and interactions revealed patterns of how requesters and responders refine queries and recommendations. Our work informs future intelligent recommender systems design.

Beyond Swipes and Scores: Investigating Practices, Challenges and User-Centered Values in Online Dating Algorithms

The reliability of online dating algorithms has sparked considerable debate, particularly regarding skepticism about their excessive emphasis on evaluating and getting evaluated, which often overshadows the quest for authentic romantic connections. To understand the multifaceted influence of dating algorithms on end-users and explore avenues for algorithmic features considering the dynamics of human relationships, we conducted a mixed-methods study comprising in-depth interviews (N = 22) and a metaphoric co-design workshop (N = 12) with active users of online dating platforms. Interviews revealed that users perceive and respond to algorithmic evaluations with varied perceptions and behaviors, often expressing concerns about the emotional burden of constant self-presentation and the pursuit of quantitative assessments over genuine connections. In the design workshop, users envisioned desired algorithmic features to overcome investigated challenges, such as prioritizing personal values, tailored matchmaking, and support for personal growth in relationships. This research contributes to unraveling the complex dynamics of human-algorithm interaction in the context of online dating. By aligning algorithmic functions more closely with user desires and relationship goals, this study paves the way for more meaningful and authentic connections in the digital dating landscape.

E-Business Online Experience, Satisfaction and Trust: Basis for Customer Loyalty among Selected SMEs in Bulacan

This research paper investigates the relationship between e-business online experience, satisfaction, and trust as predictors of customer loyalty among small and medium enterprises (SMEs) in a selected area of Bulacan. Considering the increasing reliance on digital platforms for e-commerce, issues surrounding online security and user privacy have arisen, raising concerns about consumer trust in e-business environments. Employing a quantitative research methodology, the study utilizes a quantitative descriptive and correlational design to measure and identify the mean and standard deviation of online experience, satisfaction, and trust as independent variables, with customer loyalty as the dependent variable. The findings reveal that SMEs in Bulacan have a strongly positive perception of their e-business online experience, particularly highlighting the simplicity, visual appeal, and effectiveness of the websites they use. They appreciate the quality of information provided by these e-business platforms, which facilitates e-purchases through up-to-date content and straightforward transactions. The study also indicates a strong agreement among SMEs regarding the effectiveness of e-business websites in meeting consumer expectations for repeat purchases, while also identifying areas for improvement in online performance features. Moreover, SMEs generally perceive a high level of security regarding e-business platforms, particularly regarding information transmission and electronic payment safety. However, there was a slightly lower perception of user privacy concerns. The regression analysis indicates that both e-business online experience and customer satisfaction are significant predictors of customer loyalty, underscoring the importance of enhancing these aspects to cultivate lasting customer relationships.

Online and Offline Evaluation in Search Clarification

The effectiveness of clarification question models in engaging users within search systems is currently constrained, casting doubt on their overall usefulness. To improve the performance of these models, it is crucial to employ assessment approaches that encompass both real-time feedback from users (online evaluation) and the characteristics of clarification questions evaluated through human assessment (offline evaluation). However, the relationship between online and offline evaluations has been debated in information retrieval. This study aims to investigate how this discordance holds in search clarification. We use user engagement as ground truth and employ several offline labels to investigate to what extent the offline ranked lists of clarification resemble the ideal ranked lists based on online user engagement. Contrary to the current understanding that offline evaluations fall short of supporting online evaluations, we indicate that when identifying the most engaging clarification questions from the user’s perspective, online and offline evaluations correspond with each other. We show that the query length does not influence the relationship between online and offline evaluations, and reducing uncertainty in online evaluation strengthens this relationship. We illustrate that an engaging clarification needs to excel from multiple perspectives, and SERP quality and characteristics of the clarification are equally important. We also investigate if human labels can enhance the performance of Large Language Models (LLMs) and Learning-to-Rank (LTR) models in identifying the most engaging clarification questions from the user’s perspective by incorporating offline evaluations as input features. Our results indicate that LTR models do not perform better than individual offline labels. However, GPT, an LLM, emerges as the standout performer, surpassing all LTR models and offline labels.

Convenience and price drive online pharmacy usage by veterinary clients.

To evaluate factors that influence client selection of a veterinary pharmacy and assess client perception of the impact of online pharmacies on veterinary clinics. Survey data and satisfaction metrics were compared between online pharmacies, a teaching hospital pharmacy (UW Veterinary Care), and primary care veterinary clinics between March and April 2023. Online pharmacy users were asked about perceived impact of online pharmacies on veterinary clinics. Personal values were correlated with the likelihood of using a pharmacy. 158 surveys were analyzed; 32.9% of respondents used an online pharmacy. Of those, 20% used a veterinary-affiliated online pharmacy. Convenience was the value most liked by online pharmacy and primary care clinic users. Online users reported liking price most, whereas veterinary clinic pharmacy users (UW Veterinary Care and primary care clinics) reported liking communication and trust. Online users ranked price as more important, whereas veterinary clinic users ranked personalized experience (caring, explanations, veterinary recommended) as more important. Regardless of pharmacy type, satisfaction scores were high. Most online users perceived a negative impact of online pharmacies on veterinary clinics; this did not change reported usage. Online and veterinary clinic users prioritized different values. Online users prioritized price and veterinary clinic users prioritized personalized experience. Online usage was not influenced by perceived impact. For veterinary clinics attempting to increase revenue, appealing to these 2 distinct driving values is essential. Offering practice-directed online pharmacies with competitive and transparent pricing could procure online consumers, while maintaining a personalized experience remains important for consumers purchasing prescriptions in-house.

Surveillance in the Advertising Landscape: Application of the DEAL Framework to Investigate Online Behavioral Advertising, Surveillance, and Users’ Responses on Instagram

Technology has allowed the creation of granular-level data that can provide detailed insights and analysis on consumers. This level of data allows marketers and advertisers to make better-informed decisions about their target consumers and tailor their strategies to specific customer segments. With an online experiment (N = 236), we examined how increased personalization of advertisements—more precisely the case of online behavioral ads (OBA) based on the brand match (vs. mismatch) and product match (vs. mismatch) with a previous web search—impacts consumers’ responses, avoidance, and attitudes mediated by perceived surveillance. The study found that perceived surveillance increases with brand match, leading to increased advertising avoidance and less positive attitudes toward the ad, product, and brand, but no relationship was found between product match and perceived surveillance, nor did it reveal an interaction effect between brand and product mismatch on perceived surveillance. This research contributes to theory by considering perceived surveillance as an antecedent to users’ responses and presents a framework to understand people’s perceptions of increased specificity of OBA ads based on previous web searches. Additionally, this study amplifies both the need to understand consumers’ responses to increased personalization and the need to balance consumers’ privacy with effective advertising strategies.

Analysis of Online User Reviews for Popular Tourist Attractions: Almaty Case

Attractions in the tourism industry are one of the components that motivate tourists to visit destinations, such as entertainment, natural, cultural, and historical richness. For such reasons, people decide to visit unique destinations and spend time there. Almaty, the largest city of Kazakhstan, is one of the significant attraction centers of the Central Asia region, offering tourists unique and pleasant features with several tourist attractions. This study aims to analyze online user reviews of tourist attractions in Almaty, Kazakhstan, using machine learning and text mining methods. The primary focus is on identifying the main thematic clusters of reviews and their sentiment and comparing these themes with the types of attractions: historical, natural, and man-made. A total of 7,515 reviews were collected from the TripAdvisor website. The data was processed using sentiment analysis, topic modeling, and hierarchical clustering methods. The analysis revealed that 38% of the reviews were related to natural attractions, 34% to man-made, and 28% to historical ones. The most positive reviews were associated with natural attractions, while historical and man-made attractions received 79.38% and 81.40% positive reviews, respectively. In addition, the items that make up these attractions are identified, and their sentiment levels are pointed out. In addition to this situation, visitors have the most positive expressions for natural attractions, especially landscapes and lakes. The findings emphasize the importance of considering review themes to improve the quality of tourist services and to enhance the positive image of Almaty as a tourist destination.

Evaluating Long-Term Outcomes of Children Undergoing Surgical Treatment for Congenital Heart Disease for National Audit in England and Wales.

There is strong interest in the evaluation of longer-term outcome metrics for congenital heart diseases (CHDs); however, registries focus on postoperative metrics. Informed by user online discussion forums and scoping of national data, we selected sentinel CHDs and long-term outcome metrics suitable for routine monitoring. We then developed sentinel CHD phenotypes and algorithms for identifying treatment pathway procedures using clinical codes. Finally, we calculated the metrics within a retrospective national cohort analysis. The 9 selected sentinel CHDs had a higher-than-average prevalence, typically involved surgery in infancy, and were associated with an increased risk of late mortality. The selected metrics of survival and reinterventions at 1, 5, and 10 years were both important and feasible. The cohort included 29 319 (41.3% of all operated CHD births) English and Welsh children born with sentinel CHDs in 2000 to 2022. Example metrics at age 10 years included: survival-hypoplastic left heart syndrome: 57.6% (95% CI, 54.9%-60.4%), functionally univentricular heart: 86.7% (95% CI, 84.6%-88.9%), transposition of the great arteries: 93.1% (95% CI, 92.2%-93.9%), pulmonary atresia: 81.0% (95% CI, 79.1%-82.9%), atrioventricular septal defect: 88.5% (95% CI, 87.5%-89.5%), tetralogy of Fallot: 95.1% (95% CI, 94.4%-95.8%), aortic stenosis: 94.4% (95% CI, 93.3%-95.6%), coarctation: 96.7% (95% CI, 96.2%-97.3%), and ventricular septal defect: 96.9% 95% CI, (96.4%-97.3%); and (2) cumulative incidence of reintervention-hypoplastic left heart syndrome : 54.5% (95% CI, 51.5%-57.3%), functionally univentricular heart: 57.3% (95% CI, 53.9%-60.5%), transposition of the great arteries: 20.9% (95% CI, 19.5%-22.3%), pulmonary atresia: 66.8% (95% CI, 64.2%-69.1%), atrioventricular septal defect: 21.6% (20.3%-23.0%), tetralogy of Fallot: 26.6% (95% CI, 25.2%-28.0%), aortic stenosis: 31.2% (95% CI, 28.8%-33.6%), coarctation: 19.8% (95% CI, 18.6%-21.1%), and ventricular septal defect: 6.1% (95% CI, 5.5%-6.8%). It is feasible to report important long-term outcomes of survival and reintervention for sentinel CHDs using routinely collected procedure records, adding value to national audit.

Unveiling mechanism of SNSs addiction on wellbeing: the moderating role of loneliness and social anxiety

ABSTRACT Social networking sites (SNSs) play a crucial role in the lives of online users. This research aims to investigate the underlying mechanisms of SNS addiction and its subsequent impact on the wellbeing of online users. Employing the Stimulus-Organism-Response (SOR) model, we examine the influence of perceived enjoyment, utilitarian needs, and social influence on SNSs addiction and its associated consequences. Additionally, we consider the boundary conditions of loneliness as the predictors of SNSs addiction and social anxiety in the association between SNSs addiction and strain. We collected data (Time 1 and II) from 558 SNSs users using an online survey. By employing structural equation modelling via Smart PLS 4.0, our findings indicate that perceived enjoyment, utilitarian needs, and social influence significantly contribute to SNSs addiction. Furthermore, SNS addiction is positively correlated with strain, which positively triggers users’ wellbeing. We also found a significant positive moderating effect of loneliness and social anxiety on the proposed relationships. Overall, this study enhances our understanding of the theoretical foundations and multifaceted influences contributing to the literature on SNSs addiction and its impact on wellbeing through strain. It also acknowledges the study's limitations and suggests directions for future research.

The Arctic Twittersphere and the Russian Invasion of Ukraine

Social media use has grown in popularity in recent years, becoming a primary source of information for many. Several scholarly inquiries have analyzed how the Arctic region has been portrayed in traditional media. However, no study has comprehensively detailed how the region has been presented on social media. The objective of this article is to sketch the contours of the Arctic discussion on Twitter and to inquire whether significant geopolitical events impact the nature of the online discussion. Using tweets on Arctic issues published between January 2020 and August 2022, we assessed the timing, prevalence, and nature of messages about the circumpolar North. Overall, the Arctic conversation on Twitter is first and foremost an Arctic climate conversation, focusing on climate change, Arctic sea ice, and permafrost thawing. Climate issues are the most salient ones and are treated independently from other topics by online users. We assessed whether the Russian invasion of Ukraine changed this dominance. We found that the Arctic Twittersphere remained still predominantly focused on climate issues, although the invasion increased Arctic military security discussions dissociated from other diplomatic or natural-resources considerations.

A Product’s Kansei Appearance Design Method Based on Conditional-Controlled AI Image Generation

Accurately grasping users’ Kansei needs and rapidly transforming them into product design solutions are key factors in enhancing product competitiveness and sustainability. This paper proposes a product appearance design method based on Kansei engineering and AI image generation technology, integrating other approaches, with household indoor hydroponics as the research subject. First, the web crawler is used to obtain product image samples and user online reviews, and factor analysis (FA) is applied to quickly extract users’ Kansei needs. Second, product morphology is used to deconstruct and encode product appearances. Partial least squares regression (PLSR) is then employed to map and quantify the relationships between Kansei needs and design elements, yielding optimal design solutions and one-dimensional sketches. These sketches are subsequently used as controlled conditions in Stable Diffusion (SD), combined with a team-trained Lora model, to generate two-dimensional colored sketches in batches. Finally, evaluations verify that the generated design solutions are satisfactory and meet users’ Kansei needs. The results indicate that the proposed product appearance design method not only holds significant implications for the sustainable development of Kansei engineering in product design but also greatly enhances the efficiency of the design process, providing new insights into integrating new technologies and scientific research methods in the field of product design.

Weaving narrative threads with social psychological processes: Narrative modulations in online consumer reviews of a medical memoir

With the growing prevalence of health and illness narratives on digital platforms, research examining the social psychological processes involved in these storytelling environments remains scarce. This paper addresses this research gap by conducting a mixed-methods study of digital storytelling within the UK’s healthcare context, focusing on online consumer reviews of the medical memoir, Do no harm: stories of life, death and brain surgery (Marsh, 2014). Utilising computer-assisted text analysis methods of LIWC-22 and the Sketch Engine, linguistic cues for cognitive, affective, social and perceptual processes are identified in a corpus of online consumer reviews. A subsequent qualitative analysis, based on ‘narrative modulation’ (Huang, 2024, 2020), investigates the role of these processes in constructing and developing storylines across the user reviews. Finally, the study explores how consumer reviews in the form of ‘small stories’ challenge canonical narratives in the UK’s healthcare services. This research advances the field of narrative studies by emphasising the role of social psychological processes (Chung and Pennebaker, 2019) in modulating emerging, evolving and counter narratives in digital storytelling. The findings reveal an instrumental role of social psychological processes, as signalled by linguistic cues, in shaping narrative threads in online user reviews. This study not only develops narrative modulation as a valuable concept for narrative analysis, but also underscores its effectiveness when combined with computer-assisted text analysis tools for in-depth examinations of narrative data. Furthermore, it provides critical insights into digital storytelling in healthcare contexts, promoting knowledge transfer across narrative studies, stylistics, social psychology and medical humanities.

Quantifying drivers of virtual reality acceptance in tourism planning using a grey system theory-based approach

PurposeThis study examines the role of Virtual Reality (VR) in tourism marketing, analyzing its psychological effects, demographic differences and factors influencing adoption. It seeks to identify and measure the main drivers and obstacles to VR acceptance, improving predictions of adoption trends in tourism planning and experiences across various demographics.Design/methodology/approachThis study employs a quantitative method, blending statistical analysis with Grey System Theory. It analyzes data from VR-experienced participants using ANOVA, regression models and dynamic grey relational analysis to produce actionable insights. Data were collected from July to September 2023 from participants experienced with VR in tourism.FindingsUser engagement, positive word-of-mouth and a desire for immersive experiences drive VR acceptance, especially among frequent travelers and tech enthusiasts. While VR can enhance trip enjoyment, its long-term impact varies. To increase VR adoption in tourism, strategies include targeting frequent travelers and online users, creating accessible and engaging content, leveraging positive feedback and partnering with influencers to develop interactive VR experiences that mitigate travel planning uncertainties and attract specific user groups.Practical implicationsThe study demonstrates how VR can expand access to tourism for those unable to travel, enhance engagement and streamline planning. By leveraging VR in marketing, providers can create immersive, targeted content, reduce uncertainties, attract tech-savvy travelers and boost appeal through influencer partnerships.Originality/valueThis study pioneers the integration of Grey System Theory with traditional statistical methods to elucidate the dynamics of VR adoption in tourism. By uniquely combining ANOVA, regression models and dynamic grey relational analysis, it offers a precise model to interpret complex data, highlighting the nuanced effects of demographic factors on technology acceptance. This approach not only advances the analytical frameworks in tourism marketing but also provides critical insights into the demographic and psychological drivers of VR adoption.

Understanding the Representation of Asians and Asian Americans Within Academic Otolaryngology Leadership.

Elucidate the representation of Asian and Asian Americans in academic otolaryngology and the influence of race on promotion and leadership opportunities. Retrospective analysis of the Association of American Medical Colleges Faculty Administrative Management Online User System. Full-time otolaryngology faculty from all US medical schools from 2020 to 2023. Faculty demographics, tenure, and rank were collected. Descriptive statistics, Fischer's exact test, Rank Equity Index (REI), and multivariable logistic and ordinal regressions were used to characterize our cohort and assess the impact of race on academic advancement and leadership, defined as promotion to tenure or full professorship. Asians comprised 20.53% of 9056 faculty over 4 years. Asians were most likely to hold tenure-eligible positions (n = 600, 30.74%) but were significantly less likely than non-Asians to be tenured (43.00% vs 48.65%, P = .015). Asians were slightly above parity in promotion from assistant to associate professor (REI = 1.09) but below parity in promotion from associate professor to professor (REI = 0.78). Relative to whites, Hispanics, and African Americans, Asians reported the lowest associate/professor and assistant/professor REIs. On multivariable regressions, Asian race was not associated with decreased odds of tenure-eligible positions but was associated with decreased odds of tenure (odds ratio [OR] = 0.77, 95% confidence interval [CI] = [0.64-0.93]) and rank promotion (OR = 0.82, 95% CI = [0.74-0.90]). Despite strong overall representation in otolaryngology, Asians are less likely to receive promotion, tenure, or full professorship relative to other racial groups. Future efforts should emphasize equitable advancement opportunities to ensure a diverse otolaryngology leadership.

The Effect of Stressful Life Events on Online Privacy Protective Behavior of Israeli Students

ABSTRACTThis exploratory study investigates the influence of stressful life events on privacy‐protective behavior. We examine the effects of the ongoing state of war in Israel on the rate of deliberate falsification of personal details during website registration, in a user study of 107 students at Israeli universities. The students were queried using a quantitative method in online closed‐ended questionnaires. This research builds on our previous work (Weinberger & Bouhnik, 2021) examining the effects of other stressful life events, specifically the COVID‐19 pandemic, on the privacy‐protective behavior of Israeli students. We found that distrust of website operators and the desire to remain anonymous are the most common reasons for identity falsification. In addition, our analysis showed that the greater the concern over privacy, the more likely identity falsification was to occur. The Israel‐Hamas War in Israel seems to have exacerbated privacy concerns among online users, in turn increasing the tendency of users to exhibit privacy‐protective behavior.

Personalized multi-head self-attention network for news recommendation

With the rapid explosion of online news and user population, personalized news recommender systems have proved to be efficient ways of alleviating information overload problems by suggesting information which attracts users in line with their tastes. Exploring relationships among words and news is critical to structurally model users’ latent tastes including interested domains, while selecting informative words and news can directly reflect users’ interests. Most of the current studies do not provide an effective framework that combines distilling users’ interested latent spaces and explicit points systematically. Moreover, introducing more advanced techniques to merely chase accuracy has become a universal phenomenon. In this study, we design a Personalized Multi-Head Self-Attention Network (PMSN) for news recommendation, which combines multi-head self-attention network with personalized attention mechanism from both word and news levels. Multi-head self-attention mechanism is used to model interactions among words and news, exploring latent interests. Personalized attention mechanism is applied by embedding users’ IDs to highlight informative words and news, which can enhance the interpretability of personalization. Comprehensive experiments conducted using two real-world datasets demonstrate that PMSN efficiently outperforms state-of-the-art methods in terms of recommendation accuracy, without complicated structure design and exhausted even external resources consumption. Furthermore, visualized case study validates that attention mechanism indeed increases the interpretability.

Updates to the wild bird abundance and movement models for the early warning system for avian influenza in the EU

Abstract Highly pathogenic avian influenza (HPAI) viruses pose a significant threat to both poultry and wild bird populations. Migratory wild birds play a key role in the intercontinental spread of avian influenza (AI), introducing the virus into poultry populations. In response to frequent AI outbreaks in Europe, the European Food Safety Authority (EFSA), at the request of the European Commission (EC), produces quarterly and annual epidemiological reports to monitor and analyse AI trends. A key component of this surveillance includes the integration of outbreak data from Member States and contributions from non‐governmental ornithological organisations like the European Bird Census Council (EBCC) and the European Union for Bird Ringing (EURING) together in a predictive spatio‐temporal risk assessment model. Previous data integration and modelling efforts led to the development of an early warning system for predicting HPAI outbreaks accessible through a publicly available online user interface: the Bird Flu Radar. This report presents an improvement of the system by expanding the species coverage and refining the existing base models behind the epidemiological model. Specifically, this report details the exploration to incorporate 12 additional wild bird species into the models, and the changes made to the base models predicting the distribution and movements of wild birds. We demonstrate the improvements respecting the existing base models while at the same time enhancing the effectiveness in predicting HPAI outbreaks and possibly mitigating negative effects in Europe by providing more accurate predictions to different stakeholders.

Reflective and Formative Indicators of Information Credibility on Social Media

ABSTRACTAs part of a larger project to develop a scale for measuring web credibility perceptions, this poster reports on preliminary findings of a literature analysis to identify reflective and formative indicators of information credibility on social media. Of 90 papers found by a systematic database search and screening, this poster examines 20 papers focused on information credibility on microblogs (e.g., Twitter, Weibo) as a popular source for online users' information seeking. Our analysis identified 22 reflective indicators (e.g., fair, accurate) and 31 formative indicators (e.g., reputable, attractive), eight (e.g., trustworthy, unbiased) of which overlapped. Given the intertwined, often blurred border between these two sets of items, the coding scheme developed in the present study can help determine the relevance and type of the items. Future research directions are discussed.