How do personality traits affect communication among users in online social networks?

Identification and Prediction of Human Behavior through Mining of Unstructured Textual Data

The identification of human behavior can provide useful information across multiple job spectra. Recent advances in applying data-based approaches to social sciences have increased the feasibility of modeling human behavior. In particular, studying human behavior by analyzing unstructured textual data has recently received considerable attention because of the abundance of textual data. The main objective of the present study was to discuss the primary methods for identifying and predicting human behavior through the mining of unstructured textual data. Of the 823 articles analyzed, 87 met the predefined inclusion criteria and were included in the literature review. Our results show that the included articles could be symmetrically classified into two groups. The first group of articles attempted to identify the leading indicators of human behavior in unstructured textual data. In this group, the data-based approaches had three main components: (1) collecting self-reported survey data, (2) collecting data from social media and extracting data features, and (3) applying correlation analysis to evaluate the relationship between two sets of data. In contrast, the second group focused on the accuracy of data-based approaches for predicting human behavior. In this group, the data-based approaches could be categorized into (1) approaches based on labeled unstructured textual data and (2) approaches based on unlabeled unstructured textual data. The review provides a comprehensive insight into unstructured textual data mining to identify and predict human behavior and personality traits.

Triggers and strategies related to the collaborative information-seeking behaviour of researchers in ResearchGate

Purpose

The purpose of this paper is to identify the triggers, strategies and outcomes of collaborative information-seeking behaviours of researchers on the ResearchGate social networking site.

Design/methodology/approach

Data were collected from the population of researchers who use ResearchGate. The sample was limited to the Ph.D. students and assistant professors in the library and information science domain. Qualitative interviews were used for data collection.

Findings

Based on the findings of the study, informal communications and complex information needs lead to a decision to use collaborative information-seeking behaviour. Also, easy access to sources of information and finding relevant information were the major positive factors contributing to collaborative information-seeking behaviour of the ResearchGate users. Users moved from collaborative Q&A strategies to sharing information, synthesising information and networking strategies based on their needs. Analysis of information-seeking behaviour showed that ResearchGate users bridged the information gap by internalizing new knowledge, making collaborative decisions and increasing their work's visibility.

Originality/value

As one of the initial studies on the collaborative information-seeking behaviour of ResearchGate users, this study provides a holistic picture of different triggers that affect researchers' information-seeking on ResearchGate.

What drives Instagram usage? User motives and personality traits

Purpose

Social networking sites (SNS) have become extensively used communication environments as a result of the advancements in online technologies, and among various SNS platforms, Instagram is currently the most prominent image-based network. Since usage motives for alternative SNS environments with different outstanding benefits are expected to vary, this study has focused mainly on extracting the key context-specific usage motives of Instagram. Another purpose of this study is to figure out personality traits differences among Instagram user segments.

Design/methodology/approach

An online survey was designed, and a total of 690 fully completed questionnaires was collected, and 507 of the respondents were Instagram users. After conducting factor analysis, six main usage motive categories have been revealed and named as self-expression, recording, socialization, recreation, creativity, and prying.

Findings

Instagram users have been clustered as passionate, distant, and spectator users based on their usage motives. Ultimately, personality differences among these clusters have been explored using the Big Five Inventory (BFI) and two additional traits, social interaction anxiety, and fear of negative evaluation. Openness to experience, social interaction anxiety, and fear of negative evaluation were found to be significantly different among these clusters.

Originality/value

Discovering the motives of SNS usage, segmenting users based on these motives, and then portraying the personality traits of each segment gives important clues about how SNSs can better design their interfaces and generate content for attracting users in different segments.

Phones, privacy, and predictions

Purpose

Mobile phones have become one of the most favored devices to maintain social connections as well as logging digital information about personal lives. The privacy of the metadata being generated in this process has been a topic of intense debate over the last few years, but most of the debate has been focused on stonewalling such data. At the same time, such metadata is already being used to automatically infer a user’s preferences for commercial products, media, or political agencies. The purpose of this paper is to understand the predictive power of phone usage features on individual privacy attitudes.

Design/methodology/approach

The present study uses a mixed-method approach, involving analysis of mobile phone metadata, self-reported survey on privacy attitudes and semi-structured interviews. This paper analyzes the interconnections between user’s social and behavioral data as obtained via their phone with their self-reported privacy attitudes and interprets them based on the semi-structured interviews.

Findings

The findings from the study suggest that an analysis of mobile phone metadata reveals vital clues to a person’s privacy attitudes. This study finds that multiple phone signals have significant predictive power on an individual’s privacy attitudes. The results motivate a newer direction of automatically inferring a user’s privacy attitudes by leveraging their phone usage information.

Practical implications

An ability to automatically infer a user’s privacy attitudes could allow users to utilize their own phone metadata to get automatic recommendations for privacy settings appropriate for them. This study offers information scientists, government agencies and mobile app developers, an understanding of user privacy needs, helping them create apps that take these traits into account.

Originality/value

The primary value of this paper lies in providing a better understanding of the predictive power of phone usage features on individual privacy attitudes.

Influence of personality traits on open access mode of publishing

Purpose

The purpose of this paper is to assess the influence of personality traits on perception and acceptance of open access (OA) mode of publishing by the author community of University of Kashmir, India. The study is an attempt to highlight the relationship between personality traits of authors and OA mode of publishing.

Design/methodology/approach

The study is based on the responses of 48 faculty members affiliated with different Departments of Science Discipline of University of Kashmir. Big Five personality traits (extraversion, agreeableness, conscientiousness, emotional stability and openness to experience) were tapped through ten-item personality inventory, and information regarding OA was gauged through six self-devised statements.

Findings

Pearson correlation test confirms statistically significant relation between personality traits and different dimensions of OA mode of publishing. Personality traits are found to have an influence on author’s perception of OA mode of publishing. However, the study could not ascertain any relation between the notions of an author about the quality of OA content with any of the personality traits. Emotionally stable authors are found to explicitly submit their work in OA journals without any anxiety or negativity. Agreeable and conscientious authors also prefer to keep their work open to make it helpful to the broader audience and get maximum recognition from peers and citations to their work respectively. However, some authors (agreeable) hesitate in submitting their work in open platforms due to the fear of getting their works easily copied.

Originality/value

The study is first of its kind highlighting a new dimension in the field of OA and investigates the influence of personality traits on author’s attitude towards open mode of publishing.

Gillenson M. How to keep brand fan page followers? The lens of person-environment fit theory

Purpose

Companies create brand fan pages (BFPs) on social media platforms to broadcast product information, increase brand awareness and engage customers. A common challenge facing BFPs is how to attract and retain followers effectively. Through the lens of the theory of person–environment fit (TPEF), the purpose of this paper is to develop and validate a theoretical model to explain the role of multidimensional fit perceptions in cultivating BFP users’ continued following intention.

Design/methodology/approach

Data collected from 193 active followers of BFPs on Sina Weibo, the most prevalent social media platform in China, were used to test the proposed model. The partial least squares method was employed to assess the relationships in the model.

Findings

The findings reveal that users will continue to follow the BFP if their needs align with what the BFP provides, and if they perceive their values and characteristics to match those of the brand and fellow followers.

Originality/value

This study is among the first to extend the research context of the TPEF from organizational behaviors to examining how perceived fit influences users’ continued intention to follow in the social media context. In addition to the theoretical contributions, the findings of this study have important implications for practitioners who undertake social media management or user behavior analysis.

Personality Homophily and Geographic Distance in Facebook

Personality homophily remains an understudied aspect of social networks, with the traditional focus concerning sociodemographic variables as the basis for assortativity, rather than psychological dispositions. We consider the effect of personality homophily on one of the biggest constraints to human social networks: geographic distance. We use the Big Five model of personality to make predictions for each of the five facets: Openness to experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. Using a network of 313,669 Facebook users, we investigate the difference in geographic distance between homophilous pairs, in which both users scored similarly on a particular facet, and mixed pairs. In accordance with our hypotheses, we find that pairs of open and conscientious users are geographically further apart than mixed pairs. Pairs of extraverts, on the other hand, tend to be geographically closer together. We find mixed results for the Neuroticism facet, and no significant effects for the Agreeableness facet. The results are discussed in the context of personality homophily and the impact of geographic distance on social connections.

Compulsive mobile application usage and technostress: the role of personality traits

Purpose

Compulsive usage of mobile applications may have a negative effect on people’s health and social interaction. Past studies have indicated that personality traits were related to compulsive usage of technologies, but most of them have explored the factors from the system and interface design perspectives, specifically. The purpose of this paper is to explore how the Big Five personality traits, materialism, and external locus of control affect compulsive mobile application usage, and examines how compulsive usage impacts technostress.

Design/methodology/approach

The present study proposes a framework based on Big Five personality traits and related literature. The author collected a total of 546 valid responses to the online survey, and the author examined the 18 proposed hypotheses using SmartPLS software.

Findings

The results show that neuroticism, extraversion, materialism, and external locus of control have significant effects on compulsive usage of mobile social applications. In addition, agreeableness, materialism, and external locus of control significantly influence compulsive usage of mobile game applications. Compulsive usage (of both mobile social apps and mobile games), materialism, and external locus of control all have a positive, direct impact on technostress.

Practical implications

This study offers mobile app design companies and educational institutions a understanding of the social problems caused by the misuse of mobile devices, helping them to prevent the increase of the negative influences of such misuse.

Originality/value

The primary value of this paper lies in providing a better understanding of the influence of personality traits on the compulsive use of mobile apps and technostress.

What Is Seen Is Who You Are: Are Cues in Selfie Pictures Related to Personality Characteristics?

Developments and innovation in the areas of mobile information technology, digital media and social networks foster new reflections on computer-mediated communication research, especially in the field of self-presentation. In this context, the selfie as a self-portrait photo is interesting, because as a meaningful gesture, it actively and directly relates the content of the photo to the author of the picture. From the perspective of the selfie as an image and the impression it forms, in the first part of the research we explored the distinctive characteristics of selfie pictures; moreover, from the perspective of the potential reflection of a selfie image on the personality of its author, in the second part we related the characteristics of selfie pictures to various personality constructs (e.g., Big Five personality traits narcissism and femininity-masculinity). Important aspects of selfies especially in relation to gender include the tilt of the head, the side of the face exhibited, mood and head position, later related also to the context of the selfie picture. We found no significant relations between selfie cues and personality constructs. The face-ism index was related to entitlement, and selfie availability to neuroticism.

Influence of knowledge transfer on SNS community cohesiveness

Purpose

The purpose of this paper is to examine whether social networking site (SNS) communities benefit from collective knowledge and collaboration, which represent a portfolio of knowledge transfer on SNSs.

Design/methodology/approach

A survey was conducted on a large scale through an online questionnaire. Structural equation modeling was employed to analyze data collected from 674 experienced SNS users.

Findings

The results indicate that all three exogenous variables, presented as user characteristics and integrated into SNS user characteristics, were positively related to the knowledge transfer portfolio, namely, to collective knowledge and collaboration, and these variables had significant moderating effects on SNS users’ community cohesiveness. Early SNS adoption was more likely than late SNS adoption to moderate the relationship between collective knowledge and community cohesiveness and that between collective collaboration and community cohesiveness.

Practical implications

The findings provide useful insights for SNS operators to enhance the process of collaborative knowledge transfer. They may also be used to obtain better insights into important factors that require closer attention during SNS use.

Originality/value

The present study provides a systematic analysis of SNS use by considering a new research model and investigating the effects of SNS-based knowledge transfer on user outcomes based on three major characteristics of SNS users. The results are expected to provide a major foundation for further SNS research and a better understanding of the relationships between SNS user characteristics, knowledge transfer, and community cohesiveness.

Adoption of mobile social networking sites for learning?

Purpose

– The purpose of this paper is to explore the factors that influence users’ behavioral intention (BI) to adopt mobile social networking sites (mSNS) in facilitating formal/informal learning. Specifically, the study also investigates the association of mobility, reachability and convenience with performance expectancy (PE) and effort expectancy (EE).

Design/methodology/approach

– Partial least squares structural equation modeling (PLS-SEM) approach was applied to test on 266 valid responses.

Findings

– The findings indicated that learning compatibility (LC), PE, EE and copyright clearance (CC) has a significant effect on BI. The results also revealed that EE is influenced by mobility, reachability and convenience. PE however was found to be influenced by convenience.

Practical implications

– The results of this study provides valuable insights and references for practitioners and mobile network providers in developing mSNS in facilitating learning.

Originality/value

– While mSNS have the potential to become a new research area with numerous benefits for the learning community, there is little research on the adoption factors on mSNS in facilitating learning. This study therefore attempts to close the research gap by contributing to the mobile literatures.