scholarly journals A Semantic Scale Network analysis of the revised Mystical Experiences Questionnaire: A call for collaboration

2021 ◽  
Author(s):  
Mitch Earleywine ◽  
Fiona Low ◽  
Joseph De Leo
Keyword(s):  
Network Analysis ◽  
Discriminant Validity ◽  
Subjective Effects ◽  
Incremental Validity ◽  
Therapeutic Effects ◽  
Subjective Responses ◽  
Network Analyses ◽  
Scale Network ◽  
Mystical Experiences ◽  
And Gender

Abstract Background and aims Multiple laboratories have proposed measures of subjective effects of psychedelics as potential mediators of their therapeutic impact. Other work has identified individual differences that covary with subjective responses in informative ways. The range of potential measures of responses, traits, and outcomes is vast. Ideas for new measures are likely numerous. The field will progress efficiently if proposed new scales can add incremental validity. Semantic Scale Network analyses identify conceptual overlap among scales based on items (rather than participant ratings), which could help laboratories avoid putting effort into measures that are unlikely to account for unique variance. Semantic Scale Network analyses can also reveal links to constructs from disparate research literatures, potentially helping investigators generate novel hypotheses and explain connections among disparate findings. The results of Semantic Scale Network analyses have the potential to improve as more investigators enter their scales into the corpus. Method Example analyses using the revised Mystical Experiences Questionnaire (MEQ) underscore the uniqueness and discriminant validity of the MEQ subscales. Results Findings dovetail with published theorizing and suggest potentially novel links with different therapeutic effects. The MEQ total or subscales overlap with measures of awe, inspiration, regret, dissatisfaction, transcendence, depression, fatigue, and spirituality. Links with measures of stress, alexithymia, and gender identity suggest lines of further work. Conclusions This analytic approach might suggest unique applications for psychedelic-assisted treatments and provide perspectives on phenomena outside the field. As psychedelic researchers enter their scales to the corpus for Semantic Scale Network analyses, the field will benefit.

scholarly journals The Young Positive Schema Questionnaire (YPSQ): German Validation, Domain Structure, and Network Analysis in Patients and Matched Controls

2020 ◽  
Author(s):  
Andreas Paetsch ◽  
Josefine Moultrie ◽  
Nils Kappelmann ◽  
Julia Fietz ◽  
David P. Bernstein ◽  
...  
Keyword(s):  
Network Analysis ◽  
Domain Structure ◽  
Psychiatric Patients ◽  
Network Connectivity ◽  
Incremental Validity ◽  
Psychometric Validation ◽  
Social Belonging ◽  
And Gender ◽  
Order Domain ◽  
Schema Questionnaire

Early Adaptive Schemas (EAS) are resilience-oriented counterparts to Early Maladaptive Schemas, which are central in Schema Therapy. The Young Positive Schema Questionnaire (YPSQ) was developed to measure 14 EAS. The higher-order domain structure of negative schemas is frequently used in research and clinical practice but has not yet been empirically investigated for EAS. Objectives of the present study were therefore: (1) Psychometric validation of a German translation of the YPSQ; (2) Replication of EMS domain structure and examination of EAS domain structure via factor analysis; (3) Exploratory description of the EAS network-structure. Participants were 128 psychiatric patients and 256 controls, matched on age and gender, resulting in a mixed sample of N = 384. Regarding psychometric properties, the German YPSQ exhibited satisfying factorial validity, construct and incremental validity, and internal consistency. The examination of the domain structure revealed three domains: Connection & Acceptance, Unimpaired Autonomy & Performance, and Balanced Standards & Adequate Limits. In exploratory network analysis, Optimism was identified as a globally-central schema, while Competence, Emotional Fulfilment, Social Belonging, and Realistic Expectations appeared especially connected within their respective domain. Optimism and Competence were, however, less central in psychiatric patients compared to controls, while Stable Attachment was of increased centrality. Lastly, patients exhibited an overall weaker network connectivity in EAS, suggesting that positive schemas may in general be less readily activated in psychiatric patients compared to controls.

Large-Scale Network Analysis for Online Social Brand Advertising

MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
◽  
Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
◽  
...  
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Large Scale Network ◽  
Brand Advertising ◽  
Scale Network

An evaluation of DSM-5 Section III Personality Disorder Criterion A (Impairment) in accounting for psychopathology

2018 ◽  
Author(s):  
Chelsea Sleep ◽  
Donald Lynam ◽  
Thomas A. Widiger ◽  
Michael L Crowe ◽  
Josh Miller
Keyword(s):  
Personality Disorders ◽  
Discriminant Validity ◽  
Factor Model ◽  
Incremental Validity ◽  
Self Report ◽  
Statistical Prediction ◽  
Dsm 5 ◽  
Criterion A ◽  
Personality Dysfunction ◽  
Axis I

An alternative diagnostic model of personality disorders (AMPD) was introduced in DSM-5 that diagnoses PDs based on the presence of personality impairment (Criterion A) and pathological personality traits (Criterion B). Research examining Criterion A has been limited to date, due to the lack of a specific measure to assess it; this changed, however, with the recent publication of a self-report assessment of personality dysfunction as defined by Criterion A (Levels of Personality Functioning Scale – Self-report; LPFS-SR; Morey, 2017). The aim of the current study was to test several key propositions regarding the role of Criterion A in the AMPD including the underlying factor structure of the LPFS-SR, the discriminant validity of the hypothesized factors, whether Criterion A distinguishes personality psychopathology from Axis I symptoms, the overlap between Criterion A and B, and the incremental predictive utility of Criterion A and B in the statistical prediction of traditional PD symptom counts. Neither a single factor model nor an a priori four-factor model of dysfunction fit the data well. The LPFS-SR dimensions were highly interrelated and manifested little evidence of discriminant validity. In addition, the impairment dimensions manifested robust correlations with measures of both Axis I and II constructs, challenging the notion that personality dysfunction is unique to PDs. Finally, multivariate regression analyses suggested that the traits account for substantially more unique variance in DSM-5 Section II PDs than does personality impairment. These results provide important information as to the functioning of the two main components of the DSM-5 AMPD and raise questions about whether the model may need revision moving forward.Keywords: dysfunction, impairment, personality disorders, Section III, incremental validity Public Significance: The alternative model of personality disorders included in Section III of the 5th addition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) includes two primary components: personality dysfunction and maladaptive traits. The current results raise questions about how a new, DSM-5 aligned measure of personality dysfunction operates with regard its factor structure, discriminant validity, ability to differentiate between personality and non-personality based forms of psychopathology, and incremental validity in the statistical prediction of traditional DSM personality disorders.

scholarly journals “Splendid Isolation”: The reproduction of music industry inequalities in Spotify’s recommendation system

2021 ◽  
pp. 146144482110221
Author(s):  
Tamas Tofalvy ◽  
Júlia Koltai
Keyword(s):  
Network Analysis ◽  
Recommendation System ◽  
Music Industry ◽  
Country Of Origin ◽  
Small Scale ◽  
Primary Determinant ◽  
Scale Network ◽  
Splendid Isolation

In this article, we argue that offline inequalities, such as core–periphery relations of the music industry, are reproduced by streaming platforms. First, we offer an overview of the reproduction of inequalities and core–periphery dynamics in the music industry. Then we illustrate this through a small-scale network analysis case study of Hungarian metal bands’ connections on Spotify. We show that the primary determinant of a given band’s international connectedness in Spotify’s algorithmic ecosystem is their international label connections. Bands on international labels have more reciprocal international connections and are more likely to be recommended based on actual genre similarity. However, bands signed with local labels or self-published tend to have domestic connections and to be paired with other artists by Spotify’s recommendation system according to their country of origin.

scholarly journals Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a Dutch cultural controversy on Twitter

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256696
Author(s):  
Anna Keuchenius ◽  
Petter Törnberg ◽  
Justus Uitermark
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Network Analysis ◽  
Language Processing ◽  
User Interaction ◽  
User Interactions ◽  
Online Interactions ◽  
Network Analyses ◽  
Social Media Platforms ◽  
Signed Network

Despite the prevalence of disagreement between users on social media platforms, studies of online debates typically only look at positive online interactions, represented as networks with positive ties. In this paper, we hypothesize that the systematic neglect of conflict that these network analyses induce leads to misleading results on polarized debates. We introduce an approach to bring in negative user-to-user interaction, by analyzing online debates using signed networks with positive and negative ties. We apply this approach to the Dutch Twitter debate on ‘Black Pete’—an annual Dutch celebration with racist characteristics. Using a dataset of 430,000 tweets, we apply natural language processing and machine learning to identify: (i) users’ stance in the debate; and (ii) whether the interaction between users is positive (supportive) or negative (antagonistic). Comparing the resulting signed network with its unsigned counterpart, the retweet network, we find that traditional unsigned approaches distort debates by conflating conflict with indifference, and that the inclusion of negative ties changes and enriches our understanding of coalitions and division within the debate. Our analysis reveals that some groups are attacking each other, while others rather seem to be located in fragmented Twitter spaces. Our approach identifies new network positions of individuals that correspond to roles in the debate, such as leaders and scapegoats. These findings show that representing the polarity of user interactions as signs of ties in networks substantively changes the conclusions drawn from polarized social media activity, which has important implications for various fields studying online debates using network analysis.

scholarly journals Studying Positive and Negative Direct and Extended Contact: Complementing Self-Reports With Social Network Analysis

2017 ◽  
Vol 43 (11) ◽  
pp. 1566-1581 ◽  
Author(s):  
Ralf Wölfer ◽  
Eva Jaspers ◽  
Danielle Blaylock ◽  
Clarissa Wigoder ◽  
Joanne Hughes ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Intergroup Relations ◽  
Large Scale ◽  
Intergroup Contact ◽  
Network Analyses ◽  
Self Reports ◽  
Extended Contact ◽  
Contact Parameters

Traditionally, studies of intergroup contact have primarily relied on self-reports, which constitute a valid method for studying intergroup contact, but has limitations, especially if researchers are interested in negative or extended contact. In three studies, we apply social network analyses to generate alternative contact parameters. Studies 1 and 2 examine self-reported and network-based parameters of positive and negative contact using cross-sectional datasets ( N = 291, N = 258), indicating that both methods help explain intergroup relations. Study 3 examines positive and negative direct and extended contact using the previously validated network-based contact parameters in a large-scale, international, and longitudinal dataset ( N = 12,988), demonstrating that positive and negative direct and extended contact all uniquely predict intergroup relations (i.e., intergroup attitudes and future outgroup contact). Findings highlight the value of social network analysis for examining the full complexity of contact including positive and negative forms of direct and extended contact.

scholarly journals Information sharing in supply chains: a review of risks and opportunities using the systematic literature network analysis (SLNA)

2019 ◽  
Vol 24 (1) ◽  
pp. 5-21 ◽  
Author(s):  
Claudia Colicchia ◽  
Alessandro Creazza ◽  
Carlo Noè ◽  
Fernanda Strozzi
Keyword(s):  
Supply Chain ◽  
Network Analysis ◽  
Literature Review ◽  
Supply Chains ◽  
Information Sharing ◽  
Content Type ◽  
Network Analyses ◽  
Dynamic Representation ◽  
Research Areas ◽  
Over Time

Purpose The purpose of this paper is to identify and discuss the most important research areas on information sharing in supply chains and related risks, taking into account their evolution over time. This paper sheds light on what is happening today and what the trajectories for the future are, with particular respect to the implications for supply chain management. Design/methodology/approach The dynamic literature review method called Systematic Literature Network Analysis (SLNA) was adopted. It combines the Systematic Literature Review approach and bibliographic network analyses, and it relies on objective measures and algorithms to perform quantitative literature-based detection of emerging topics. Findings The focus of the literature seems to be on threats that are internal to the extended supply chain rather than on external attacks, such as viruses, traditionally related to information technology (IT). The main arising risk appears to be the intentional or non-intentional leakage of information. Also, papers analyze the implications for information sharing coming from “soft” factors such as trust and collaboration among supply chain partners. Opportunities are also highlighted and include how information sharing can be leveraged to confront disruptions and increase resilience. Research limitations/implications The adopted methodology allows for providing an original perspective on the investigated topic, that is, how information sharing in supply chains and related risks are evolving over time because of the turbulent advances in technology. Practical implications Emergent and highly critical risks related to information sharing are highlighted to support the design of supply chain risks strategies. Also, critical areas to the development of “beyond-the-dyad” initiatives to manage information sharing risks emerge. Opportunities coming from information sharing that are less known and exploited by companies are provided. Originality/value This paper focuses on the supply chain perspective rather than the traditional IT-based view of information sharing. According to this perspective, this paper provides a dynamic representation of the literature on the investigated topic. This is an important contribution to the topic of information sharing in supply chains is continuously evolving and shaping new supply chain models.

Steady Flow Calculations Using Transient Analysis Combined With Network Analysis

2003 ◽  
Author(s):  
Masashi Shimada ◽  
Ryota Kurisu
Keyword(s):  
Network Analysis ◽  
Transient Analysis ◽  
Steady Flows ◽  
Speed Of Convergence ◽  
Wave Speeds ◽  
Network Analyses ◽  
Cpu Time ◽  
Friction Factors ◽  
Optimization Parameter ◽  
Time Marching

This paper proposes a method of solving steady flows in large pipelines with the transient analysis (MOC) combined with the network analysis. The existing methods of accelerating the speed of convergence to steady flows in pipelines, i.e., the time marching approach (TMA) replaces the system dimensions (lengths of pipes, friction factors, wave speeds) by not actual ones and dynamically controls one optimization parameter to reduce the spectral radius. That method will be applied to two pipeline systems having a few thousand of pipes. To accelerate much more the convergence the graph-theoretical information used in the network analyses is implemented. From the discharges computed with TMA the heads at each node are adequately modified using the information of “Tree” of the directed-graph defined for pipelines. Two variations of the method are also proposed. They reduces much the Cpu time to solve steady flows in large pipelines.

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