Posting Activities Research Articles

Designing Games for GDPR: Negotiating Understandings of GDPR in EU Schools

In this study we combine a participatory design process with a citizen science framing, to foster a dialogue on GDPR in the school. We focus on the perspective of students, approaching them as co-researchers, in designing and evaluating a series of apps, aimed at spreading knowledge on GDPR. We have created a design space between secondary school students in Denmark and Italy, to gather insights across different countries. Results show that approaching students as designers and testers enabled them to provide honest and concrete insights on their experience with GDPR. We identified a detachment related to their posting activities, caused by how social media platforms (SoMe) challenge the boundaries between their personal and school-related ecologies.

Designing Games for GDPR: Negotiating Understandings of GDPR in EU Schools.

In this study we combine a participatory design process with a citizen science framing, to foster a dialogue on GDPR in the school. We focus on the perspective of students, approaching them as co-researchers, in designing and evaluating a series of apps, aimed at spreading knowledge on GDPR. We have created a design space between secondary school students in Denmark and Italy, to gather insights across different countries. Results show that approaching students as designers and testers enabled them to provide honest and concrete insights on their experience with GDPR. We identified a detachment related to their posting activities, caused by how social media platforms (SoMe) challenge the boundaries between their personal and school-related ecologies.

Local information advantage and stock returns: Evidence from social media

AbstractWe examine the information asymmetry between local and nonlocal investors with a large dataset of stock message board postings. We document that abnormal relative postings of a firm, that is, unusual changes in the volume of postings from local versus nonlocal investors, capture locals' information advantage. This measure positively predicts firms' short‐term stock returns as well as those of peer firms in the same city. Sentiment analysis shows that posting activities primarily reflect good news, potentially due to social transmission bias and short‐sales constraints. We identify the information driving return predictability through content‐based analysis. Abnormal relative postings also lead analysts' forecast revisions. Overall, investors' interactions on social media contain valuable geography‐based private information.

The Tweetology of New and Renewable Energy in Indonesia

The amount of unstructured data is increasing annually, which is promising forgaining insights. Twitter, a platform producing unstructured data, is currently one of the mostpopular media platforms used for conducting research on a topic's trend. This study attempts toanalyze the topic of New and Renewable Energy (NRE) in Indonesia. The purpose of this studyis to gain insights into the NRE topic trend over the last ten years by modeling the topicsdiscussed on Twitter and examining the location distribution of users who post tweets about thetopic. Accordingly, this study employed descriptive analysis, geocoding analysis, and topicmodeling. The results of descriptive analysis show that the development of NRE has acceleratedin recent years, particularly in 2021. Geocoding analysis reveals that the distribution of peoplewho engage in NRE posting activities is dominated by DKI Jakarta province. Topic modelingyielding two topics that were discussed the most by Indonesians over a 10-year period. The twotopics are related to government policies that support the development of NRE and electricity,which is Indonesia's focus in NRE. This study highlights the importance of analyzing theTweetology of NRE.

Dashboard Monitoring Website Dosen Studi Kasus Universitas Bina Darma

The concept of dashboard performance is an information system application model provided for managers to present performance quality information, from a company or organizational institution, dashboards have been widely adopted by companies or businesses. In this study, the authors designed a dashboard that was used as a monitoring system for lecturer posting activities at Binadarma University, Palembang. The limitation of the dashboard in this study only displays data based on lecturer posts which will be developed in the form of a website. Dashboard design is more effective and efficient than viewing data manually, which requires managers to open a database to view data one by one from lecturers' posts. In making the lecturer website dashboard, the data taken is in the form of posting data stored in the lecturer database, the data that has been taken will be presented in the dashboard in the form of graphs, tables and dashboards.

멀티미디어 온라인 게시판 Padlet의 학습 효과성에 대한 대학생 학습자들의 인식

This study examines college students’ perceptions of the learning effectiveness of multimedia bulletin boards. Through various online bulletin board activities using multimedia, the research investigated how students perceived the learning effect of this type of online tool, Padlet. Fifty-four first-year students performed five different posting activities using Padlet and responded to the questionnaire about the learning advantages they recognized. Their responses were analyzed both quantitatively and qualitatively. The concepts of learning effectiveness of Padlet activities were coded and classified into three categories: emotional, cognitive, and social constructivist. Results showed that students mentioned emotional factors the most, followed by social constructivist factors. The students described that posting activities using multimedia increased their learning motivation; they could effectively share their thoughts with other students and better understand their peers’ideas. Their perception of the cognitive domain related to the improvement of language ability was the least. students are expected to improve the cognitive skills related to language learning if they are provided with appropriate activities according to learning topics.

How Social Media Analytics Can Inform Content Strategies

ABSTRACT Social media has become a strategic tool for businesses and nonprofit organizations to connect with audiences. However, no comprehensive framework exists to support the continued improvement of social media outcomes. This work draws on prior studies related to social media analytics and user engagement to develop an overarching, analytics-driven process for social content strategy development and improvement. The process provides firms with a set of procedures to regularly assess competitors’ and possibly their own content topic posting activities. It then outlines steps to measure the influence of content topics and post characteristics on engagement outcomes and use the garnered insights to drive future posting activities. A proof-of-concept case in the healthcare context is presented to demonstrate the feasibility of the proposed process.

The Relationship Between Posting and Photo Manipulation Activities on Social Networking Sites and Internalization of a Tanned Ideal Among Australian Adolescents and Young Adults

We examined whether sharing photos on social networking sites and, in particular, the approach to sharing photos online were associated with internalization of a tanned ideal and appearance comparisons. Adolescents and young adults ( N = 587) completed measures of social networking site use, photo activities, internalization, and appearance comparisons. Regular photo-sharers internalized a tanned ideal to a greater extent and reported engaging in more frequent appearance comparisons to people in media than participants who did not regularly share photos online. Internalization was associated with editing photos prior to posting, whereas appearance comparisons were associated with investment, measured as the concern for the quality and effort expended in selecting photos (e.g., carefully selecting a photo, taking a photo specifically for posting) and editing photos prior to posting. Future interventions to reduce the risk of skin cancer should address users’ investment in the quality of photos they share online and the desire to manipulate photos to adhere to appearance ideals.

User modeling and usage profiling based on temporal posting behavior in OSNs

In this paper, we study the posting behavior of online social network (OSN) users, in particular the posting frequency and temporal patterns, and consider possible interpretations of how users use the platform. At the aggregate (macro) level, we find two distinct peaks of traffic, one during morning working hours, and one in the evening. The morning peak is more pronounced for frequent posters, while the evening peak is pronounced for the remaining users. We postulate that this difference results from different usage purposes of the OSN platform (e.g. for work, with customers, etc.) than purely social interactions (e.g., friends, family, etc.). We also study user posting behavior at an individual (micro) level and model the user posting sequences as generated by a Hidden Markov Model. We compare the results of using a simple zeroth order model (which is equivalent to a topic model such as LDA), and a first-order model, in terms of their effectiveness in clustering and predicting user types, and show the advantage gained by the first-order HMM. Overall, our study provides new insights into user activity in today’s OSNs, and suggests a framework for profiling users based on their posting activities. We believe our approach will complement other methods of user profiling based on static demographic information and friendship network information.

FuSeO: Fuzzy semantic overlapping community detection

5 Abstract. Finding community structures in online social networks is an important methodology for understanding the internal organization of users and actions. Most previous studies have focused on structural properties to detect communities. They do not analyze the information gathered from the posting activities of members of social networks, nor do they consider overlapping communities. To tackle these two drawbacks, a new overlapping community detection method involving social activities and semantic analysis is proposed. This work applies a fuzzy membership to detect overlapping communities with different extent and run semantic analysis to include information contained in posts. The available resource description format contributes to research in social networks. Based on this new understanding of social networks, this approach can be adopted for large online social networks and for social portals, such as forums, that are not based on network topology. The efficiency and feasibility of this method is verified by the available experimental analysis. The results obtained by the tests on real networks indicate that the proposed approach can be effective in discovering labelled and overlapping communities with a high amount of modularity. This approach is fast enough to process very large and dense social networks. 6 7 8 9 10 11 12 13 14 15 16

Lessons Learned for Online Health Community Moderator Roles: A Mixed-Methods Study of Moderators Resigning From WebMD Communities.

BackgroundOnline health community (OHC) moderators help facilitate conversations and provide information to members. However, the necessity of the moderator in helping members achieve goals by providing the support they need remains unclear, with some prior research suggesting that moderation is unnecessary or even harmful for close-knit OHCs. Similarly, members’ perceptions of moderator roles are underexplored. Starting January of 2013, WebMD moderators stopped working for WebMD communities. This event provided an opportunity for us to study the perceived role of moderators in OHCs.ObjectiveWe examine the OHC members’ perception on OHC moderators by studying their reactions toward the departure of moderators in their communities. We also analyzed the relative posting activity on OHCs before and after the departure of moderators from the communities among all members and those who discussed moderators’ departures.MethodsWe applied a mixed-methods approach to study the posts of all 55 moderated WebMD communities by querying the terms relating to discussions surrounding moderators’ disappearance from the WebMD community. We performed open and axial coding and affinity diagramming to thematically analyze patients’ reactions to the disappeared moderators. The number of posts and poster groups (members and moderators) were analyzed over time to understand posting patterns around moderators’ departure.ResultsOf 821 posts retrieved under 95 threads, a total of 166 open codes were generated. The codes were then grouped into 2 main themes with 6 total subthemes. First, patients attempted to understand why moderators had left and what could be done to fill the void left by the missing moderators. During these discussions, the posts revealed that patients believed that moderators played critical roles in the communities by making the communities vibrant and healthy, finding solutions, and giving medical information. Some patients felt personally attached with moderators, expressing they would cease their community participation. On the other hand, patients also indicated that moderators were not useful or sometimes even harmful for peer interactions. The overall communities’ posting activity, which was already in decline, showed no significant difference before and after the moderators’ departure. In fact, the overall posting activities of the communities were declining well before the moderators’ departure. These declining posting activities might be the reason why WebMD removed the moderators.ConclusionCompassionate moderators who provide medical expertise, control destructive member posts, and help answer questions can provide important support for patient engagement in OHCs. Moderators are in general received positively by community members and do not appear to interfere with peer interactions. Members are well aware of the possibility of misinformation spreading in OHCs. Further investigation into the attitudes of less vocal community members should be conducted.

Walls-in-one: usage and temporal patterns in a social media aggregator.

The continual launches of new online social media that meet the most varied people’s needs are resulting in a simultaneous adoption of different social platforms. As a consequence people are pushed to handle their identity across multiple platforms. However, due the to specialization of the services, people’s identity and behavior are often partial, incomplete and scattered in different “places”. To overcome this identity fragmentation and to give an all-around picture of people’s online behavior, in this paper we perform a multidimensional analysis of users across multiple social media sites. Our study relies on a new rich dataset collecting information about how and when users post their favorite contents, about their centrality on different social media and about the choice of their username. Specifically we gathered the posting activities and social sites usage from Alternion, a social media aggregator.The analysis of social media usage shows that Alternion data reflect the novel trend of today’s users of branching out into different social platforms. However the novelty is the multidimensional and longitudinal nature of the dataset. Having at our disposal users’ degree in five different social networks, we performed a rank correlation analysis on users’ degree centrality and we find that the degrees of a given user are scarcely correlated. This is suggesting that the individuals’ importance changes from medium to medium. The longitudinal nature of the dataset has been exploited to investigate the posting activity. We find a slightly positive correlation on how often users publish on different social media and we confirm the burstiness of the posting activities extending it to multidimensional time-series. Finally we show that users tend to use similar usernames to keep their identifiability across social sites.

Behavior analysis methods for Twitter users based on transitions in posting activities

Purpose – The purpose of this paper is to activate latent users posts by modeling user behaviors by a transition of clusters that represent particular posting activities. Twitter has rapidly spread and become an easy and convenient microblog that enables users to exchange instant text messages called tweets. There are so many latent users whose posting activities have decreased. Design/methodology/approach – Under this model, two kinds of time-series analysis methods are proposed to clarify the lifecycles of Twitter users. In the first one, all users belong to a cluster consisting of several features at individual time slots and move among the clusters in a time series. In the second one, the posting activities of Twitter users are analyzed by the amount of tweets that vary with time. Findings – This sophisticated evaluation using a large actual tweet-set demonstrated the proposed methods effectiveness. The authors found a big difference in the state transition diagrams between long- and short-term users. Analysis of short-term users introduces effective knowledge for encouraging continued Twitter use. Originality/value – An the efficient user behavior model, which describes transitions of posting activities, is proposed. Two kinds of time longitudinal analysis method are evaluated using a large amount of actual tweets.

Chinese Journalists' Discursive Weibo Practices in an Extended Journalistic Sphere

This study examines Chinese journalists' Weibo practices by analyzing 2659 Weibo posts by journalists. Previous studies indicate that Western journalists generally “normalize” their posting activities on social media to fit their professional standards and practices, but this normalization practice is conducted in a more complicated way in China. Our findings suggest that Chinese journalists' Weibo practices are influenced by four offline journalistic discourses: Party-press, professionalism, market economy, and Confucian intellectual. Overall, Chinese journalists' Weibo discourses exhibit political caution, professionalism deviation, marketing commitment, and Confucian intellectual expression. By comparing officially oriented and commercially oriented journalists, we find that commercial journalists who are subject to less political and organizational control were more politically engaged, professionalism deviant, and socially conscious. This study treats “journalists' Weibo” as a spin-off journalistic sphere. On this new technological platform, Chinese journalists are able to enjoy increased journalistic autonomy and freedom. Thus, while Chinese journalists normalize their Weibo practices based on their existing offline journalistic discourses, the spin-off sphere of Weibo provides them with new opportunities to deviate from traditional journalistic norms. Yet, we find that official political and organizational control is still tight. Thus, technological innovation and socio-political context are both important in influencing journalists' discursive practices on this extended news sphere.

Assessing Censorship on Microblogs in China: Discriminatory Keyword Analysis and the Real-Name Registration Policy

The authors investigated censorship practices and the use of microblogs-or weibos, in Chinese-using 111 million microblogs collected between 1 January and 30 June 2012. To better control for alternative explanations for censorship decisions attributable to an individual's characteristics and choices, they used a matched case-control study design to determine a list of Chinese terms that discriminate censored and uncensored posts written by the same microbloggers. This list includes homophones and puns created by Chinese microbloggers to circumvent the censors successfully. The study's design also made it possible to evaluate the real-name registration system's impact on microbloggers' posting activities. Findings suggest that the new policy might have stopped some microbloggers from writing about social and political subjects.

User-Centric Organization of Search Results

The authors investigated the use of microblogs - or weibos - and related censorship practices using 111 million microblogs collected between 1 January and 30 June 2012. Using a matched case-control study design helped researchers determine a list of Chinese terms that discriminate censored and uncensored posts written by the same microbloggers. This list includes homophones and puns created by Chinese microbloggers to circumvent the censors successfully. The study's design also allowed for evaluating the new real-name registration system's impact on microbloggers' posting activities. Findings suggest that this policy might have stopped some microbloggers from writing about social and political subjects.

Intrinsic vs. Image-Related Utility in Social Media: Why Do People Contribute Content to Twitter?

We empirically study the motivations of users to contribute content to social media in the context of the popular microblogging site Twitter. We focus on noncommercial users who do not benefit financially from their contributions. Previous literature suggests that there are two main types of utility that motivate these users to post content: intrinsic utility and image-related utility. We leverage the fact that these two types of utility give rise to different predictions as to whether users should increase their contributions when their number of followers increases. To address the issue that the number of followers is endogenous, we conducted a field experiment in which we exogenously added followers (or follow requests, in the case of protected accounts) to a set of users over a period of time and compared their posting activities to those of a control group. We estimated each treated user's utility function using a dynamic discrete choice model. Although our results are consistent with both types of utility being at play, our model suggests that image-related utility is larger for most users. We discuss the implications of our findings for the evolution of Twitter and the type of value firms may derive from such platforms in the future.

Understanding human dynamics in microblog posting activities

Human activity patterns are an important issue in behavior dynamics research. Empirical evidence indicates that human activity patterns can be characterized by a heavy-tailed inter-event time distribution. However, most researchers give an understanding by only modeling the power-law feature of the inter-event time distribution, and those overlooked non-power-law features are likely to be nontrivial. In this work, we propose a behavior dynamics model, called the finite memory model, in which humans adaptively change their activity rates based on a finite memory of recent activities, which is driven by inherent individual interest. Theoretical analysis shows a finite memory model can properly explain various heavy-tailed inter-event time distributions, including a regular power law and some non-power-law deviations. To validate the model, we carry out an empirical study based on microblogging activity from thousands of microbloggers in the Celebrity Hall of the Sina microblog. The results show further that the model is reasonably effective. We conclude that finite memory is an effective dynamics element to describe the heavy-tailed human activity pattern.

Online talk: does it matter?

PurposeThe purpose of this paper is to examine stocks that are most actively discussed by online posters and see if the messages posted about these stocks have information or if they are just noise.Design/methodology/approachThis study uses messages posted on TheLion.com, which reports a real time list of the ten most actively discussed stocks. The stocks in this list at the daily market close during 2005‐2006 are examined. An event study is performed to estimate the daily abnormal returns on these stocks. Contemporaneous and lead–lag regressions of abnormal returns against message posting activities are performed.FindingsOnline posters prefer thinly traded micro‐cap stocks. On average, there is an abnormal return of 19.4 per cent on a stock the day it is one of the ten most talked about stocks. The number of messages posted about a stock on a given day is not only positively related with the stock's abnormal return on that day but it also positively predicts the next day's abnormal return.Research limitations/implicationsIt may be interesting to examine if the investor sentiment expressed in online messages has predictive power for micro‐cap stocks.Practical implicationsThe results provide evidence to regulators that online talk affects stock prices. They show investors that there are inefficiencies in the stock market. They also suggest that corporate managers, especially of small firms, should monitor the stock message boards.Originality/valueThis study focuses on the micro‐cap stocks favored by online posters and finds that online talk has the power to predict the next‐day returns.