Study Of Human Behavior Research Articles

Reproducible research practices and transparency across linguistics

Scientific studies of language span across many disciplines and provide evidence for social,  cultural, cognitive, technological, and biomedical studies of human nature and behavior. As it becomes increasingly empirical and quantitative, linguistics has been facing challenges and limitations of the scientific practices that pose barriers to reproducibility and replicability. One of the  proposed solutions to the widely acknowledged reproducibility and replicability crisis has been the implementation of transparency practices,  e.g., open access publishing, preregistrations, sharing study materials, data, and analyses, performing study replications, and declaring conflicts of interest. Here, we have assessed the prevalence of these practices in 600 randomly sampled journal articles from linguistics across two time points. In line with similar studies in other disciplines, we found that 35% of the articles were published open access and the rates of sharing materials, data, and protocols were below 10%. None of the articles reported preregistrations, 1% reported replications, and 10% had conflict of interest statements. These rates have not increased noticeably between 2008/2009 and 2018/2019, pointing to remaining barriers and the slow adoption of open and reproducible research practices in linguistics. To facilitate adoption of these practices, we provide a range of recommendations and solutions for implementing transparency and improving reproducibility of research in linguistics.

Model dan Proses Komunikasi

Psychological and mechanistic paradigms are two different approaches to understanding and explaining human phenomena and the world around them. The psychology paradigm involves the study of human thoughts, behavior, and mental processes. This approach focuses on understanding how individuals think, feel, and act. Psychological paradigms include various theories and methods used to study human psychological aspects. On the other hand, the mechanistic paradigm involves the view that the world can be explained and understood through the principles of mechanics and causality. These two paradigms have differences in the way they view and explain human phenomena and the world. The psychological paradigm focuses more on the psychological and mental aspects of humans, while the mechanistic paradigm focuses more on the physical and mechanical aspects

Can competing demands affect pro-environmental behaviour: a study of the impact of exposure to partly related sequential experiments

The study of human behaviour is central to the development of appropriate policies for sustainability. We argue that mathematical models of human choice behaviour may produce biased results if they fail to account for the possibility of spillover effects, in particular the possibility that individual behaviour may change as a result of interventions along with competing demands (multiple demands), such as in the sequential exposure to partly related choice contexts. Using a sample of 751 individuals and a carefully constructed experiment, we develop mathematical models that jointly explain the choice between different pro-environmental actions and the willingness to donate money for environmental causes, and at the same time, allow us to test the indirect effect of exposure to multiple demands. We find that the strength of preferences for behavioural changes leading to greater CO2 reductions is (causally) shaped by participants previously considering other similar behavioural changes. The kind of spillover effects we find are relatively complex and often subtle, and thus warrant further replication studies. Care was taken to account for variation of tastes, formatting, order and learning effects, thus reducing the risk of the spillover-related results being influenced by differences across individuals in environmental preferences. Our study demonstrates the existence of a specific type of spillover effects, namely how prior exposure to related choice contexts may affect behaviour in subsequent settings and showcased the effectiveness of discrete choice models to test for it. Given our results, we believe that spillover effects need to be taken into account in the broader choice modelling literature, and at the same time we showcase a useful experimental framework for environmental psychologists and economists.

MBTI-BASED PERSONALITY PREDICTION FROM TEXT USING MACHINE LEARNING TECHNIQUES

Personality prediction research seeks to define and comprehend the nuanced differences in human behavioural tendencies, thought patterns, and emotional expressions. Utilizing an array of methodologies, including psychological assessments, behavioural observations, and computational modelling, researchers aim to anticipate and clarify an individuals distinctive personality traits and characteristics. Natural Language Toolkit (NLTK) approaches are used to preprocess and translate text data into numerical features that can be predicted by machine learning models. The aim of this work is to predict the personality type of an individual linked to their posts and to explore the relevance of the test in the study and categorization of human behaviour using learning models. With the aid of a machine learning model and dataset, the main objective of this research is to determine a persons Myers-Briggs Type Indicator (MBTI) personality type based on their postings. This involves utilizing various methodologies, including psychological assessments and computational modelling, to analyse and classify the unique personality traits and characteristics associated with each MBTI type. The research aims to contribute valuable insights into understanding human behaviour and leveraging machine learning for predictive personality analysis. KEYWORDS: Myers-Briggs Type Indicator, Machine Learning Models, Natural Language Toolkit

Differences in malaria vector biting behavior and changing vulnerability to malaria transmission in contrasting ecosystems of western Kenya

BackgroundDesigning, implementing, and upscaling of effective malaria vector control strategies necessitates an understanding of when and where transmission occurs. This study assessed the biting patterns of potentially infectious malaria vectors at various hours, locations, and associated human behaviors in different ecological settings in western Kenya.MethodsHourly indoor and outdoor catches of human-biting mosquitoes were sampled from 19:00 to 07:00 for four consecutive nights in four houses per village. The human behavior study was conducted via questionnaire surveys and observations. Species within the Anopheles gambiae complex and Anopheles funestus group were distinguished by polymerase chain reaction (PCR) and the presence of Plasmodium falciparum circumsporozoite proteins (CSP) determined by enzyme-linked immunosorbent assay (ELISA).ResultsAltogether, 2037 adult female anophelines were collected comprising the An. funestus group (76.7%), An. gambiae sensu lato (22.8%), and Anopheles coustani (0.5%). PCR results revealed that Anopheles arabiensis constituted 80.5% and 79% of the An. gambiae s.l. samples analyzed from the lowland sites (Ahero and Kisian, respectively). Anopheles gambiae sensu stricto (hereafter An. gambiae) (98.1%) was the dominant species in the highland site (Kimaeti). All the An. funestus s.l. analyzed belonged to An. funestus s.s. (hereafter An. funestus). Indoor biting densities of An. gambiae s.l. and An. funestus exceeded the outdoor biting densities in all sites. The peak biting occurred in early morning between 04:30 and 06:30 in the lowlands for An. funestus both indoors and outdoors. In the highlands, the peak biting of An. gambiae occurred between 01:00 and 02:00 indoors. Over 50% of the study population stayed outdoors from 18:00 to 22:00 and woke up at 05:00, coinciding with the times when the highest numbers of vectors were collected. The sporozoite rate was higher in vectors collected outdoors, with An. funestus being the main malaria vector in the lowlands and An. gambiae in the highlands.ConclusionThis study shows heterogeneity of anopheline distribution, high outdoor malaria transmission, and early morning peak biting activity of An. funestus when humans are not protected by bednets in the lowland sites. Additional vector control efforts targeting the behaviors of these vectors, such as the use of non-pyrethroids for indoor residual spraying and spatial repellents outdoors, are needed.Graphical

Creating frames of reference for chert exploitation during the Late Pleistocene in Southwesternmost Iberia.

Southwestern Iberia has played a key role in characterizing Late Pleistocene human ecodynamics. Among other aspects of human behavior, chert procurement and management studies in this region have received increasing attention in the past two decades, especially focusing on the sites showing repeated human occupation, such as the case of Vale Boi (Southern Portugal). However, these studies have been very limited in their geographical scope, and mostly focused on brief macroscopic descriptions of the raw materials. To further our knowledge of the relationship between regional availability of raw materials and its impact on human adaptations and mobility, a more detailed approach to characterizing geological sources is needed. This paper characterizes chert raw materials location, diversity, and availability in a geologically well-defined region of southern Portugal - the Algarve. Through macroscopic and petrographic approaches, we provide a detailed characterization of geological chert sources to build a frame of reference for chert exploitation in the region. Our results show that there are four main chert formations in Algarve, and that despite the within-source variability, sufficient differences at macroscopic and petrographic levels are present to allow clear source attribution. These results provide a baseline for raw material studies in archaeological assemblages across southwestern Iberia, that will be essential to further characterize the dynamics of human behavior in some of the most important eco-cultural niches.

Impulsive Aggression Break, Based on Early Recognition Using Spatiotemporal Features

The study of human behaviors aims to gain a deeper perception of stimuli that control decision making. To describe, explain, predict, and control behavior, human behavior can be classified as either non-aggressive or anomalous behavior. Anomalous behavior is any unusual activity; impulsive aggressive, or violent behaviors are the most harmful. The detection of such behaviors at the initial spark is critical for guiding public safety decisions and a key to its security. This paper proposes an automatic aggressive-event recognition method based on effective feature representation and analysis. The proposed approach depends on a spatiotemporal discriminative feature that combines histograms of oriented gradients and dense optical flow features. In addition, the principal component analysis (PCA) and linear discriminant analysis (LDA) techniques are used for complexity reduction. The performance of the proposed approach is analyzed on three datasets: Hockey-Fight (HF), Stony Brook University (SBU)-Kinect, and Movie-Fight (MF), with accuracy rates of 96.5%, 97.8%, and 99.6%, respectively. Also, this paper assesses and contrasts the feature engineering and learned features for impulsive aggressive event recognition. Experiments show promising results of the proposed method compared to the state of the art. The implementation of the proposed work is available here.

Pierre Janet’s Secret Garden, or the Botanical Collection of a Psychopathologist

Abstract Pierre Janet, the French philosopher, psychotherapist, and doctor (1859–1947), has often been presented as one of the central figures in contemporary clinical psychology, whose practices and ideas are said to have anticipated those of Sigmund Freud, before becoming a fierce critic of psychoanalysis. What is less well known, however, is that he was also an experienced botanist. The recent discovery of his personal herbarium, which was long thought to be lost, leads historians to address a curious paradox. Unlike his professional papers, of which only a fraction remains, his entire collection built up over 70 years of passionate collecting has been preserved. Thus although the world-famous clinician, bound to medical secrecy, still resists historical exposition, the hitherto unknown amateur naturalist appears in the full light of day. Even though Janet was careful not to hastily amalgamate the study of human behaviour to that of plants, detailed examination of his abundant written work shows that these two disciplines could overlap on occasions.

A study of a hybrid Fogg-Hook based social media addictive algorithm from the perspective of Kuwait Society

Social media applications are widely used by human population for general and special purposes. As any emerging computing technology, social media applications’ users tend to heavily use these applications in a way that they can be considered as addicted. Human behavioural studies indicate that a behaviour can be turned into a habit and end with addiction. We study two existing social media addiction algorithms and propose a hybrid algorithm that contains the metrics of both algorithms. We test the validity of our proposed algorithm on Kuwait society through a survey that measures the implementation level of each proposed metric from Kuwait society perspective. We choose four popular social media applications in Kuwait for our tests, namely, Instagram, Twitter, Snapchat, and Tiktok. Our findings confirm the validity of the proposed metrics, and show interesting facts related to the usage level of the social media applications for different groups of Kuwaiti society users, which can be further used in many social media based services in Kuwait.

Toward Comparative Collective Behavior to Discover Fundamental Mechanisms Underlying Behavior in Human Crowds and Nonhuman Animal Groups

This article provides comparative perspectives on collective behaviors that are widely found throughout the animal kingdom, ranging from insect and crustacea swarms, fish schools, bird flocks, and mammal herds to human crowds. Studies of nonhuman animal and human collective behaviors have progressed almost separately even though they have a similar history. Theoretical studies have investigated the reproduction of collective phenomena from simple inter-individual rules, and subsequent empirical and experimental studies have found diverse and complex collective behaviors that are difficult to explain with classical theoretical models. As a consequence, a wide variety of interaction rules have been proposed. To determine models to be implemented in nature and find fundamental mechanisms of collective behaviors, this paper argues that we should compare collective behaviors among various species while adopting Tinbergen’s four questions regarding mechanism, function, development, and evolution as a methodological basis. As an example of a comparative collective behavior paradigm, we introduce our studies in which a mutual anticipation mechanism inspired by nonhuman animal collective behaviors can be linked to a self-organization function in human collective behaviors. We expect that the study of comparative collective behaviors will expand, the methodology will become more sophisticated, and new perspectives regarding the multitemporal features of collective behaviors will emerge.

Tweens: A Positive Psychology Family Intervention for Adolescents with Depression- or Anxiety-related Symptomatology

Positive psychology is the scientific study of human thoughts, feelings and behaviour that focuses on building resources rather than treating illness. The current pilot study utilised qualitative methods to explore an intervention, ‘Tweens’, based on proven methods from positive psychology. Tweens was designed to be suitable for adolescents aged 11–14, who experienced symptoms of depression, anxiety, or stress. A defining feature of Tweens is that it included both the afflicted children and their parents, and is the first study to examine a positive psychology family intervention for this target group. Using Constructive Grounded Theory, this study sought to determine what meaning, if any, the participants ascribed to Tweens and how they integrated the methods into their daily lives. The study also investigated why some participants did not find the intervention meaningful or effective. The results show that the experienced meaningfulness of Tweens can be divided into three main categories: (1) A sense of belonging or togetherness, (2) The utility of the tools that were taught, and (3) An increased mindsight and learning how to choose actions mindfully. The results are discussed in light of the broaden-and-build theory: when parents and children have shared knowledge and vocabulary for talking about well-being, supportive upward spirals occur. All the adolescents did not perceive the intervention as meaningful, and we discuss variations in depressiveness, problematic life circumstances and possible flaws in the intervention as possible reasons for this.

Flexible social inference facilitates targeted social learning when rewards are not observable.

Groups coordinate more effectively when individuals are able to learn from others' successes. But acquiring such knowledge is not always easy, especially in real-world environments where success is hidden from public view. We suggest that social inference capacities may help bridge this gap, allowing individuals to update their beliefs about others' underlying knowledge and success from observable trajectories of behaviour. We compared our social inference model against simpler heuristics in three studies of human behaviour in a collective-sensing task. Experiment 1 demonstrated that average performance improved as a function of group size at a rate greater than predicted by heuristic models. Experiment 2 introduced artificial agents to evaluate how individuals selectively rely on social information. Experiment 3 generalized these findings to a more complex reward landscape. Taken together, our findings provide insight into the relationship between individual social cognition and the flexibility of collective behaviour.

Analysis of Mobile Device Dual Tasking on the Move: Normal Cognitive Decline of Aging as Ground Truth for Mild Cognitive Impairment

The widespread use of mobile phones in daily life makes them a fundamental tool for the study of human behavior. In particular, they can be used as a source of additional information to help to diagnose diseases. This work is based on contrasted dual-tasking tests where cognitive performance is studied by performing tasks of high cognitive load while walking. In this case, we study significant differences in mobile device use among groups of people of different ages and examine whether they are more characteristic when the interaction takes place on the move. A study is conducted by monitoring the interaction with the mobile device for one consecutive week and analyzing the correlations between these interactions and the participants’ ages. Additionally, a user profiling model is designed to help to use this ground truth in future works focused on the early diagnosis of cognitive deficits. The results obtained contribute to preliminarily characterizing how age-related normotypical cognitive decline affects interactions with mobile devices. In addition, the pilot study generates a dataset with monitored events and interactions of 45 users that includes more than 4.5 million records.

Hidden Markov model detection of interpersonal interaction dynamics in predicting patient depression improvement in psychotherapy: Proof-of-concept study

BackgroundPrevious human ethology studies have demonstrated that the interpersonal interactions displayed in therapy by both patients and therapists influences a patient's depression improvement. Pairing novel statistical techniques such as the hidden Markov model (HMM), interpersonal interaction dynamics can be uncovered by partitioning time into empirically-derived nonverbal behavioral states. This approach allows for better patient-therapist behavioral dynamics distinctions in predicting depression improvement and, subsequently, for the processes behind depression improvement. MethodsFor the 39 participating patients, the first 15 min of the first or second therapy session was recorded on video to examine the interpersonal interaction behaviors of patients and therapists. The video recordings were encoded for vocalization, looking and leg movement behavior events at a 1 s frequency. A Bayesian multivariate multilevel HMM was fitted on the behavioral event data. ResultsIt is demonstrated that patients that show improvement in the depression score are characterized by interpersonal interaction dynamics of hyperfocus when listening to their therapist in psychotherapy when compared to non-improving patients. The data supports evidence for the emergence of differences in interpersonal interaction dynamics through changed durations of the patient hyper focused listening states, but not through changed state-switching dynamics over time. LimitationsDue to our relatively small sample size we could not fit multilevel HMMs composed of more than three hidden states. ConclusionsWe suggest that applying HMMs will aid human ethological behavior studies in uncovering interpersonal interaction dynamics that occur in therapy and be able to use these dynamics to predict patient depression symptom improvement.

Explainable Goal Recognition: A Framework Based on Weight of Evidence

We introduce and evaluate an eXplainable goal recognition (XGR) model that uses the Weight of Evidence (WoE) framework to explain goal recognition problems. Our model provides human-centered explanations that answer `why?' and `why not?' questions. We computationally evaluate the performance of our system over eight different goal recognition domains showing it does not significantly increase the underlying recognition run time. Using a human behavioral study to obtain the ground truth from human annotators, we further show that the XGR model can successfully generate human-like explanations. We then report on a study with 40 participants who observe agents playing a Sokoban game and then receive explanations of the goal recognition output. We investigated participants’ understanding obtained by explanations through task prediction, explanation satisfaction, and trust.

Linguistic Phenomena in the Context of Psycholinguistic Analysis

In the article, analysis and generalization of theoretical and experimental data on the study of human speech behavior allow us to conditionally distinguish the following three aspects in the structure of language ability: the language mechanism or the ability to master a language (native and / or foreign), the language organization of a person or mental representation and organization in the mind of the speaker systems of signs of a natural language and the norms of their communication, the speech mechanism or the ability to carry out speech activity - to produce and perceive speech statements.

Motivational Theories and Their Relevance in Military Motivation

Motivation is an important aspect that determines human behaviour and various studies have been carried out to establish the determinants of human behaviour and its motivational aspects. Military profession offers a different set of working conditions where the magnitude of challenges is well above those found in commercial and other business organisations. The aspects of motivation are peculiar to the military profession and Military motivation is in a league of its own. Militaries across the world face physical and psychological challenges at work that most other people don't. Being armed with the right set of motivational techniques is critical for rising to the demands of such challenges and ensuring the best performance from the soldiers.
 This study aims to review the different motivational theories and determine their relevance in the context of military motivation. Four of the primary motivation theories in practice today have been reviewed for this purpose. These motivational theories include Maslow’s Hierarchy of Needs Theory, Herzberg’s Motivation-Maintenance Theory, McClelland’s Theory of Need Motivation and McGregor’s Theory X/ Theory Y. These theories show how employees can be motivated to achieve tasks set upon them in the workplace.
 The relevance of these theories to Military motivation is analysed. Given the peculiarities of the working conditions of the military and the challenges faced therein, these motivational theories can be suitably adapted to modify the functional aspects of military and institute suitable changes in the leadership styles and working mechanisms to improve motivation and enhance task achievement. It has been found that all these motivational theories are still relevant in military environment and can be factored in effectively in the Armed forces.

On why we lack confidence in some signal-detection-based analyses of confidence

Signal-detection theory (SDT) is one of the most popular frameworks for analyzing data from studies of human behavior – including investigations of confidence. SDT-based analyses of confidence deliver both standard estimates of sensitivity (d’), and a second estimate informed by high-confidence decisions – meta d’. The extent to which meta d’ estimates fall short of d’ estimates is regarded as a measure of metacognitive inefficiency, quantifying the contamination of confidence by additional noise. These analyses rely on a key but questionable assumption – that repeated exposures to an input will evoke a normally-shaped distribution of perceptual experiences (the normality assumption). Here we show, via analyses inspired by an experiment and modelling, that when distributions of experience do not conform with the normality assumption, meta d’ can be systematically underestimated relative to d'. Our data highlight that SDT-based analyses of confidence do not provide a ground truth measure of human metacognitive inefficiency. We explain why deviance from the normality assumption is especially a problem for some popular SDT-based analyses of confidence, in contrast to other analyses inspired by the SDT framework, which are more robust to violations of the normality assumption.

The shock, the coping, the resilience: smartphone application use reveals Covid-19 lockdown effects on human behaviors

Human mobility restriction policies have been widely used to contain the coronavirus disease-19 (COVID-19). However, a critical question is how these policies affect individuals’ behavioral and psychological well-being during and after confinement periods. Here, we analyze China’s five most stringent city-level lockdowns in 2021, treating them as natural experiments that allow for examining behavioral changes in millions of people through smartphone application use. We made three fundamental observations. First, the use of physical and economic activity-related apps experienced a steep decline, yet apps that provide daily necessities maintained normal usage. Second, apps that fulfilled lower-level human needs, such as working, socializing, information seeking, and entertainment, saw an immediate and substantial increase in screen time. Those that satisfied higher-level needs, such as education, only attracted delayed attention. Third, human behaviors demonstrated resilience as most routines resumed after the lockdowns were lifted. Nonetheless, long-term lifestyle changes were observed, as significant numbers of people chose to continue working and learning online, becoming “digital residents.” This study also demonstrates the capability of smartphone screen time analytics in the study of human behaviors.

This Sample Seems to Be Good Enough! Assessing Coverage and Temporal Reliability of Twitter’s Academic API

Because of its willingness to share data with academia and industry, Twitter has been the primary social media platform for scientific research as well as for consulting businesses and governments in the last decade. In recent years, a series of publications have studied and criticized Twitter's APIs and Twitter has partially adapted its existing data streams. The newest Twitter API for Academic Research allows to "access Twitter's real-time and historical public data with additional features and functionality that support collecting more precise, complete, and unbiased datasets. The main new feature of this API is the possibility of accessing the full archive of all historic Tweets. In this article, we will take a closer look at the Academic API and will try to answer two questions. First, are the datasets collected with the Academic API complete? Secondly, since Twitter's Academic API delivers historic Tweets as represented on Twitter at the time of data collection, we need to understand how much data is lost over time due to Tweet and account removal from the platform. Our work shows evidence that Twitter's Academic API can indeed create (almost) complete samples of Twitter data based on a wide variety of search terms. We also provide evidence that Twitter's data endpoint v2 delivers better samples than the previously used endpoint v1.1. Furthermore, collecting Tweets with the Academic API at the time of studying a phenomenon rather than creating local archives of stored Tweets, allows for a straightforward way of following Twitter's developer agreement. Finally, we will also discuss technical artifacts and implications of the Academic API. We hope that our work can add another layer of understanding of Twitter data collections leading to more reliable studies of human behavior via social media data.