This study investigates the provincial variations in self-expression among millions of Sina Weibo users within China, alongside the influence of ecological factors. Online social networking (OSN) ...platforms enable individuals to express themselves publicly through the use of personal Bios sections. In order to explore regional differences in self-expression, we constructed a self-expression index, grounded in the percentage of users who provided self-descriptions. To do this, we analyzed the Bios information of over 13 million users, obtaining provincial self-expression scores. Our results demonstrated that the self-expression index has face, convergent, and discriminant validity. Moreover, we discovered that several ecological factors exhibited a considerable impact on self-expression among Chinese Sina Weibo users. This research offers valuable insights into the regional variations of self-expression in China and the role of ecological factors in shaping such tendencies.
The last few years have witnessed the emergence and evolution of a vibrant research stream on a large variety of online social media network (SMN) platforms. Recognizing anonymous, yet identical ...users among multiple SMNs is still an intractable problem. Clearly, cross-platform exploration may help solve many problems in social computing in both theory and applications. Since public profiles can be duplicated and easily impersonated by users with different purposes, most current user identification resolutions, which mainly focus on text mining of users' public profiles, are fragile. Some studies have attempted to match users based on the location and timing of user content as well as writing style. However, the locations are sparse in the majority of SMNs, and writing style is difficult to discern from the short sentences of leading SMNs such as Sina Microblog and Twitter. Moreover, since online SMNs are quite symmetric, existing user identification schemes based on network structure are not effective. The real-world friend cycle is highly individual and virtually no two users share a congruent friend cycle. Therefore, it is more accurate to use a friendship structure to analyze cross-platform SMNs. Since identical users tend to set up partial similar friendship structures in different SMNs, we proposed the Friend Relationship-Based User Identification (FRUI) algorithm. FRUI calculates a match degree for all candidate User Matched Pairs (UMPs), and only UMPs with top ranks are considered as identical users. We also developed two propositions to improve the efficiency of the algorithm. Results of extensive experiments demonstrate that FRUI performs much better than current network structure-based algorithms.
Despite the importance of link prediction and identification of influencers in dynamic social media systems, the existing methodical theories are not capable of analyzing complex multilayer relations ...in social media networks which contain uncertainty. In fact, there is no theoretical exploration concurrently focused on multidimensional and interrelated entities in a fuzzy-based social media environment. To cover this gap, a neoteric generalized fuzzy hypergraph (GFH) methodology is designed using developed n-ary fuzzy relation technique that is the extension of convolutional binary fuzzy relation. Characterizing reflexive, symmetric, transitive, composition, t-cut and support techniques is carried out for multidimensional uncertain-based space. Also, a graphical approach is created in the generalized fuzzy hypergraph to assist the derivation of foundational implications and concepts. The GFH framework can be applied for the intelligent management of complex systems for sole or mass users of local and global social media platforms by adopting specific membership degree for each individual. To predict the linkages between elements, a fuzzy-based indicator FLP (fuzzy link prediction) is promoted, along with the indicator of SIR (score of interaction rate) to identify the influencers (strongest communicators) in an uncertain space. Through the FLP evaluation, the extracted data are analyzed as per the highest value of 1 for single, 3 for binary, 3.8 for triplet, and 0.9 for quaternary spaces for their probable links. Through the analysis of SIR data on the individuals’ membership degrees for the usage of social media platforms, the highest interaction value of 0.99 is correlated to a single member, while 5.42 magnitude addresses an influential person. The performance results show that the presented theoretical and structural approach, that is superior to the classical graph theories, is promising to configure intelligent expert systems, predict the likelihood of connections, detect communities, and specify the influencers in real social media platforms that contain uncertainty.
•Generalized fuzzy hypergraph model is configured based on developed fuzzy relation.•By advanced method, complex multilayer relationships with uncertainty are analyzed.•Link prediction methodology is proposed with FLP metric in dynamic social systems.•Identification of influencers is accomplished through SIR index in social networks.•Social media networks are modeled to evaluate complicated interrelated entities.
In the world of social media, people are free to choose names based on their preferences, which may potentially reflect certain levels of uniqueness. In this study, we have attempted to explore the ...possibility of applying the ecological theory of individualism/collectivism in the context of social media. We, thus, examined provincial variations in the uniqueness of nicknames among more than 13 million Sina Weibo users. Initially, the nickname uniqueness indicator was set at the provincial level. It was found that the uniqueness of nicknames was the highest in provinces with temperate climates, for example Guangdong, and the lowest in provinces with demanding climate, such as Ningxia. Regression analysis results partially supported that inhabitants in provinces with temperate climate were more likely to use unique nicknames on social media compared to those from harsh climate. This finding is significant in terms of ecology.
Online users are typically active on multiple social media networks (SMNs), which constitute a multiplex social network. With improvements in cybersecurity awareness, users increasingly choose ...different usernames and provide different profiles on different SMNs. Thus, it is becoming increasingly challenging to determine whether given accounts on different SMNs belong to the same user; this can be expressed as an interlayer link prediction problem in a multiplex network. To address the challenge of predicting interlayer links, feature or structure information is leveraged. Existing methods that use network embedding techniques to address this problem focus on learning a mapping function to unify all nodes into a common latent representation space for prediction; positional relationships between unmatched nodes and their common matched neighbors (CMNs) are not utilized. Furthermore, the layers are often modeled as unweighted graphs, ignoring the strengths of the relationships between nodes. To address these limitations, we propose a framework based on multiple types of consistency between embedding vectors (MulCEVs). In MulCEV, the traditional embedding-based method is applied to obtain the degree of consistency between the vectors representing the unmatched nodes, and a proposed distance consistency index based on the positions of nodes in each latent space provides additional clues for prediction. By associating these two types of consistency, the effective information in the latent spaces is fully utilized. In addition, MulCEV models the layers as weighted graphs to obtain representation. In this way, the higher the strength of the relationship between nodes, the more similar their embedding vectors in the latent representation space will be. The results of our experiments on several real-world and synthetic datasets demonstrate that the proposed MulCEV framework markedly outperforms current embedding-based methods, especially when the number of training iterations is small.
Work-related social media networks (SMNs) like LinkedIn introduce novel networking opportunities and features that promise to help individuals establish, extend, and maintain social capital (SC). ...Typically, work-related SMNs offer access to advanced networking features exclusively to premium users in order to encourage basic users to become paying members. Yet little is known about whether access to these advanced networking features has a causal impact on the accumulation of SC. To close this research gap, we conducted a randomized field experiment and recruited 215 freelancers in a freemium, work-related SMN. Of these recruited participants, more than 70 received a randomly assigned voucher for a free 12- month premium membership. We observe that individuals do not necessarily accumulate more SC from their ability to access advanced networking features, as the treated freelancers did not automatically change their online networking engagement. Those features only reveal their full utility if individuals are motivated to proactively engage in networking. We found that freelancers who had access to advanced networking features increased their SC by 4.609% for each unit increase on the strategic networking behavior scale. We confirmed this finding in another study utilizing a second, individual-level panel dataset covering 52,392 freelancers. We also investigated the dynamics that active vs. passive features play in SC accumulation. Based on these findings, we introduce the “theory of purposeful feature utilization”: essentially, individuals must not only possess an efficacious “networking weapon”—they also need the intent to “shoot” it.
Introduction: This study tries to visualize the Twitter activism networks and their opinion leader with the case of #FreeWestPapua activism. This study is important to find out who the opinion ...leaders and their networks are. This study also provides an overview of how the opinion leader frames opinions about #FreeWestPapua activism on Twitter.
Methods: This research used Social Media Network Analysis (SMNA). The SMNA method is the application of the Social Network Analysis (SNA) method to examine conversations on social media. Data collection and data processing are collected and visualised with Netlytic.
Findings: The results showed that there are 13 opinion leaders and all of the opinion leaders are from outside Papua. This study concluded that there is alienation in separatist activism in the case of #FreeWestPapua on Twitter. The most influential opinion leader in the separatist activism on Twitter is @VeronicaKoman who has the biggest values and is also active to frame public opinion. #FreeWestpapua activism framed Indonesia as a colonial in diagnostic framing and #FreeWestPapua as a solution in prognostic framing. To attract support from the international community, opinion leaders in #FreeWestPapua activism took advantage of the various #BlackLivesMatter issue and other international moments such as Korindo news by BBC.com.Originality: Although a lot of research on the Free Papua Movement has been done, there has never been a study explains about who opinion leaders and their networks and also how they are framed public opinion about #FreeWestPapua activism on social media.
Abstract Technologies such as Internet based social media network (SMN) websites are becoming an important part of many adult lives; however, less is known about their use in patients with ...schizophrenia. We need to determine (1) how “connected” are patients with schizophrenia?, (2) do these technologies interfere with the patient׳s illness?, and (3) do patients envision these technologies being involved in their treatment? We recruited 80 inpatients and outpatients age 18–70 with schizophrenia to complete a brief survey on the prevalence and frequency of cell phone, text messaging, computer, email, and SMN use, and associated attitudes. 56% of subjects use text messaging, 48% have an email account, and 27% of subjects use SMN sites daily, with Facebook being the most popular. Many current users agreed that these technologies help them interact/socialize more, expressed interest in receiving text messages from their doctors, and disagreed that these technologies make symptoms worse. These preliminary findings should be investigated in larger samples, but suggest that these technologies afford a unique opportunity to engage and improve treatment for some patients with schizophrenia.
Purpose
Marketing and branding literature has provided important insights into the context, environment and individual factors that shape customer brand experience. However, a holistic view on ...context and environmental influence on enhancing brand experience, specifically in the online social media network context, has not been considered. In addition, main focus of the previous research is on antecedent and consequence of brand experience rather strategy for enhancing brand experience. This paper aims to propose a contingency model for enhancing brand experience to provide a more holistic framework in the uncertain and complex nature of online social media network.
Design/methodology/approach
The proposed framework is based on previous literature that is identified and integrated to propose effectiveness of the contingent determinants on brand experience in different interactional circumstances.
Findings
The proposed framework implies that brand characteristics and interactive complexities of online social media networks cause contingency to the marketers or brands’ strategic attempt in delivering superior brand experience in online social media network context. These forces are as follows: online social media network characteristic (interactivity); brands’ co-creation characteristics (consumers’ and stakeholders’ participation); brand’s technical and operational competency (brands’ knowledge, ease of interactive platform); internal human resource characteristics (employees’ behaviour, brands culture, brands reputation); and customer interactive characteristics (customer demographic characteristics, customer motivation, customer attitude). These identified forces can be optimized to formulate strategies in the interactive medium for enhancing brand experience.
Research limitations/implications
This paper proposes a contingency model as well as research propositions that need to be validated and confirmed empirically. While narrowing down the current identified gap in brand experience literature by proposing a novel perspective to the concept, this research broadens and deepens understanding of the concept of brand experiences, how it is linked to the context and contextual factors. This contingency framework elucidates the resources that marketers, practitioners can use to enhance, limit or maintain all the dimensions within brand experience.
Originality/value
A holistic view on context and environmental influence on enhancing brand experience, specifically in the online social media network context, has not been considered so far. Although literature demonstrates the positive outcome of brand experience, little attention has been paid to enhancing customer brand experience, specifically in the context of online social media networks with various complex forces acting and influencing the way customers experience a brand.
This study focused on how students of the Faculty of Mass Communication use the social media networks, the differences between male and female students and the differences between the study levels in ...terms of using social media in academic communication and for the arrangement of various activities and events in their academic environment. The study aimed to identify the motives behind the students' use of social media, the academic activities they follow and arrange for, as well as the way they present themselves through these media. The survey method was adopted, using a questionnaire as the data collection tool. The study revealed that facebook was ranked first among the respondents, followed by the WhatsApp application. The students’ motives for using social media varied; the first motive was to communicate with their classmates in the college. The most frequently discussed topic was to know the time and date of classes and exams, followed by issues of interest to the whole batch. The results also revealed partial acceptance of the two hypotheses; there were statistically significant differences between the use of social media networks and the variable of study level. In the second hypothesis, there were also statistically significant differences between the use of social media networks and the gender variable.
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