Retracted: Antecedents and Consequences of Gender Swapping in Online Games

This study examines the reasons underlying gender swapping and its impacts on online gaming behavior. While previous studies considered gender swapping to be an abnormal or rare exception in one's self‐presentation, this study hypothesized that people swap genders as a rational choice based on practical benefits. An online survey was conducted with 318 male players of MMORPGs in Korea. Players swapped gender in games to gain benefits from other players under the condition of anonymity rather than to represent their own gender identity. Men playing female avatars displayed more socially amiable behaviors conventionally characterized as more feminine. Moreover, players were more willing to purchase virtual goods to decorate their gender swapped avatars, mediated by their emotional attachment to their avatar.     

Proteus vs. social identity effects on virtual brainstorming

ABSTRACT

Avatars are known to influence behaviour through their individual identity cues (Proteus effect) and through their shared identity cues (Social identity effect). The aim of this study was to investigate these two processes in a crossed design, in order to examine their interaction in the context of a brainstorming task. To activate the Proteus effect, we used creative avatars resembling inventors, and to make social identity salient, we made the avatars wear the traditional clothing of the participants’ school. The resulting factorial design included four conditions: creative avatars with or without social identity cues, and non-creative avatars with or without social identity cues. The results show that creative performance was higher with creative than non-creative avatars, but only in the absence of social identity cues. Furthermore, the presence of social identity cues increased social identification to the group, but this unexpectedly decreased creative performance. This result is discussed together with an analysis of the meaning of the social identity cues we used, which appeared to be unrelated to creativity. This discussion highlights that the effects of social identity cues on performance are complex and may be moderated by their meaning and the particular facet of social identity they make salient.     

Me,myself and I: The role of interactional context on self-presentation through avatars

This paper investigates whether the nature of an online environment can prime users to create avatars that emphasize particular characteristics. Participants created an avatar for one of three contrasting settings: blogging, dating or gaming. For the most part, avatars in blogging were created to accurately reflect their owners’ physical appearance, lifestyle and preferences. By contrast, participants in the dating and gaming treatments accentuated certain aspects of their avatar to reflect the tone and perceived expectations of the context. For instance, avatars in dating were made to look more attractive while avatars in gaming were made to look more intellectual. Yet, predominantly, these emphasized avatar attributes drew on participants’ self-image, and thus avatars were perceived by their owners as highly similar to themselves. The implications of these results are discussed against current frameworks of online identity and behavior. Most importantly, we use our results to extract design recommendations for improving avatar-driven applications.     

The Influence of the Avatar on Online Perceptions of Anthropomorphism, Androgyny, Credibility, Homophily, and Attraction

It has become increasingly common for Web sites and computer media to provide computer generated visual images, called avatars, to represent users and bots during online interactions. In this study, participants (N = 255) evaluated a series of avatars in a static context in terms of their androgyny, anthropomorphism, credibility, homophily, attraction, and the likelihood they would choose them during an interaction. The responses to the images were consistent with what would be predicted by uncertainty reduction theory. The results show that the masculinity or femininity (lack of androgyny) of an avatar, as well as anthropomorphism, significantly influence perceptions of avatars. Further, more anthropomorphic avatars were perceived to be more attractive and credible, and people were more likely to choose to be represented by them. Participants reported masculine avatars as less attractive than feminine avatars, and most people reported a preference for human avatars that matched their gender. Practical and theoretical implications of these results for users, designers, and researchers of avatars are discussed.     

Investigating the role of identity and gender in technology mediated learning

Instructors and trainers are increasingly using online education and technology-mediated learning (TML) to supplement or replace traditional approaches to classroom teaching. Because mandatory involvement requirements may not intrinsically motivate learners to achieve high quality learning, social factors with commitment, such as identification among group members, are especially important determinants of TML success. This article investigates an individual's social and self identities as important determinants in developing affective commitment (identification) and intrinsic motivation (perceived enjoyment) to share knowledge by email in the TML environment. Furthermore, given the recent emphasis on gender in system adoption and socio-linguistic literature, this study investigates gender as a moderating variable in the proposed model. An empirical test of the proposed model was conducted in the pilot test (n = 155) as well as the main test (n = 411). Social and self identities influence identification (R ² = 0.42) and perceived enjoyment (R ² = 0.52) of sharing knowledge by email. As expected, there are significant moderating effects of gender in these relationships in that male shows stronger effects of self identity while female shows stronger effects of social identity. The results of this study will help us understand the antecedents of effective knowledge sharing intervention in the TML environment, based on the integrated model of social identity theory, social influence theory, self determination theory and socio-linguistic literature.     

基于性别识别的分类CHMM语音识别

对语音识别进行了探讨,提出一种通过性别识别对连续隐马尔可夫模型（CHMM）分类的方法,在此基础上进行语音识别。首先,通过计算性别判定语音信号的Mel频率倒谱系数（MFCC）使用CHMM对说话人性别进行识别,然后再根据不同性别使用分类CHMM进行语音识别。最后通过实验验证了方法的有效性。     

Avatars in social media: Balancing accuracy,playfulness and embodied messages

This paper examines how users negotiate their self-presentation via an avatar used in social media. Twenty participants customised an avatar while thinking aloud. An analysis of this verbal data revealed three motivating factors that drive self-presentation: (1) avatars were used to accurately reflect their owners’ offline self; participants chose to display stable self-attributes or idealised their avatar by concealing or emphasising attributes aligned to imagined social roles, (2) the diversity of customisation options was exploited by some participants who broke free from the social rules governing self-presentation offline; others used the avatar's appearance to emotionally provoke and engage the avatar viewer and finally, (3) avatars were used as proxies; participants designed their online self in order to convey a message to a significant other.     

性别鉴别的线性可分性分析

首次从线性可分性的角度探讨了人脸图像的性别鉴别问题。通过对常用线性与非线性特征抽取方法以及一类改进的非线性特征抽取方法的对比分析及不同情况下性别鉴别的实验对比,较全面地考察了各种特征抽取方法所对应的数据的线性可分性及分类效果。首次提出从人脸肤色等角度考虑人脸图像的性别鉴别问题,并给出了指示意义较强的鉴别方法与方案建议。     

Towards gender equal access to ICT

Despite the great strides in information and communication technology (ICT) and the global and far-reaching effects of its spread, women in the Arab Gulf region, in general, and in Oman, in particular, are at a higher risk of being marginalized from today's knowledge-based economy, due to factual findings related to a traditionally male-dominated ICT sector, unequal access to training, the lack of Arabized Internet content and training, and the lack of awareness and policy advocacy, among others. This research aims to provide a gender-sensitive assessment of the ICT space in Oman and the status of women within it, and to develop the seeds of an information base that provides gender analysis of the opportunities and challenges in the ICT space. Survey results show that socio-cultural norms, the innate character issues of Omani females, access and training, and career counseling are mostly the factors that inhibit them from entering and adopting a career in ICT. The analysis and recommendations presented in this research are intended to assist policymakers who are willing and committed to reorienting ICT policy to take account of the needs, aspirations, and constraints of women in Omani society. © 2008 Wiley Periodicals, Inc.     

Recognizing users gender in social media using linguistic features

Web 2.0 and social media provide users with an opportunity to discuss and share opinions, as a result, a considerable amount of information will emerge which can be drawn upon to determine some demographic and behavioral features.This study is an attempt to predict gender, as a demographic feature, using linguistic features of data collected from the users' comments in the social media.For this purpose, a framework is proposed to predict the users' gender by counting the number of some given words including verbs, pronouns, articles, adjectives, adverbs, preposition and numbers. This framework, thereafter, was tested using the comments that readers of Los Angeles Times left and the model were observed to predict the gender with an accuracy of 66.66%. Security solution and e-marketing can use this framework respectively for authentication and niche marketing.     

The implications of a critical agenda in gender and IS research

Abstract.  This paper explores the nature of the critical agenda and endeavours to advance the critical debate by considering a particular case in point: gender and information systems (IS) research. It does so by drawing upon Chua's classic framework of outlining philosophical assumptions underpinning research and also by building upon prior work of the authors on the interconnections amongst research topic, epistemology and methodology. Specifically, it presents an argument for the benefits of adopting a critical perspective when studying gender and IS research, illustrating the additional insights that can be generated. These benefits and insights can also be mined from other areas of IS research.     

Theorising about gender and computing interventions through an evaluation framework

Despite over 20 years of intervention programmes, the gender balance in the computing profession is not improving. It has been suggested that the problem with much of the research on gender and computing is that it is under‐theorised. The contribution of this study is an evaluation framework, designed to evaluate gender and computing interventions, which will advance the theorisation of research through programme evaluation. This study was undertaken in three phases: The first involved theory building through an extensive review of the literature resulting in a conceptual framework for intervention programme evaluation. The second phase consisted of a multiple‐case study of 14 major intervention programmes in Australia. Subsequent modifications to the conceptual framework resulted in the gender and computing intervention evaluation framework. The value of the framework was confirmed in phase three by intervention experts and showed that applying the framework will help programme champions to evaluate their programmes more thoroughly. The dissemination of sound evaluation results will then enable a deeper theorisation of the issues surrounding gender and computing interventions.     

The effect of virtual sales agent (VSA) gender – product gender congruence on product advice credibility,trust in VSA and online vendor,and purchase intention

Online vendors are increasingly using virtual sales assistants (VSA), either in the form of an animated picture or a photograph of a real person, to help customers with their product-related information needs. Currently, what is known is that the use of a VSA in an online web shop results in positive outcomes such as trust and purchase intention. What remains unknown, however, is whether or not VSA gender-product gender congruence has a positive effect on customers' attitude towards the product-related advice, the VSA, and the online vendor and on customers' online purchase intention.To determine the hypothesized effect of VSA gender-product gender on variables such as trust and purchase intention, a 2 (VSA gender: male vs female)–×–3 (product gender: male, female, and neutral) experiment with 183 inhabitants (between the age of 18 and 30) of the Netherlands was implemented. Results of the multivariate analysis of variance (MANOVA) reveal that congruence between VSA gender and product gender (e.g. female VSA providing advice about a feminine product) positively influences customers' belief in the credibility of the product-related advice, their trust in the VSA and the online vendor, and their purchase intention. The separate main effects of VSA gender and product gender on the aforementioned dependent variables, however, are not statistically significant. Furthermore, customers' gender did not serve any moderating function in the relationship between VSA gender-product gender congruence and the dependent variables.     

基于多层特征融合可调监督函数卷积神经网络的人脸性别识别

为了进一步提高性别识别的准确率,提出了一种基于多层特征融合与可调监督函数机制的结合的卷积神经网络（L-MFCNN）模型,并将之用于人脸性别识别。与传统卷积神经网络（CNN）不同,L-MFCNN将多个浅层中间卷积层特征输出与最后卷积层特征输出相结合,融合多层卷积层的特征,不仅利用了深层卷积的整体语义信息,还考虑了浅层卷积的细节局部纹理信息,使得性别识别更加准确。此外L-MFCNN还引入具有可调目标监督函数机制的Large-Margin Softmax Loss作为输出层,利用其调节不同的间隔（margin）的机制来有效引导深层卷积网络学习,使得同种性别间的类内间距更小,不同性别间的类间距更大,获得更好的性别识别效果。在多个人脸数据集上的性别识别实验结果表明,L-MFCNN的识别准确率要高于其他传统的卷积网络模型。L-MFCNN模型也为将来的人脸性别识别研究提供了新的思路与方向。     

A comparative analysis of different gender pair combinations in pair programming

Over the last decade, there has been a steady stream of pair programming studies. However, one significant area of pair programming that has not received its due attention is gender. Considering the fact that pair programming is one of the major human-centric software development paradigms, this is a gap that needs to be addressed. This empirical study conducted quantitative and qualitative analyses of different gender pair combinations within pair programming context. Using a pool of university programming course students as the experiment participants, the study examined three gender pair types: female–female, female–male, and male–male. The result revealed that there was no significant gender difference in the pair programming coding output. But there were significant differences in the levels of pair compatibility and communication between the same gender pair type: female–female and male–male, and the mixed gender pair type, female–male. The post-experiment comments provide additional insights and details about gender in pair interactions.     

基于改进CNN的年龄和性别识别

人脸图像的年龄和性别识别是人脸分析的重要任务,在真实多变场景下完成识别依然面临挑战。改进深度卷积神经网络（Convolutional Neural Network,CNN）,将首层大尺寸卷积核替换为级联3[×]3卷积核;采用跨连卷积层融合中层和高层抽象特征;加入Batch Normalization（BN）层,设置较高的学习率和较小的Dropout比率;采用1[×]1卷积核与全局平均池化（Global Average Pooling）取代全连接层。实验表明,所提方法与主流的年龄性别识别方法比较具有较好的识别率,在Adience数据集上,年龄识别精度达到89.8%,性别识别精度达到93.3%。     

Improving the SVM gender classification accuracy using clustering and incremental learning

Gender recognition has been playing a very important role in various applications such as human–computer interaction, surveillance, and security. Nonlinear support vector machines (SVMs) were investigated for the identification of gender using the Face Recognition Technology (FERET) image face database. It was shown that SVM classifiers outperform the traditional pattern classifiers (linear, quadratic, Fisher linear discriminant, and nearest neighbour). In this context, this paper aims to improve the SVM classification accuracy in the gender classification system and propose new models for a better performance. We have evaluated different SVM learning algorithms; the SVM‐radial basis function with a 5% outlier fraction outperformed other SVM classifiers. We have examined the effectiveness of different feature selection methods. AdaBoost performs better than the other feature selection methods in selecting the most discriminating features. We have proposed two classification methods that focus on training subsets of images among the training images. Method 1 combines the outcome of different classifiers based on different image subsets, whereas method 2 is based on clustering the training data and building a classifier for each cluster. Experimental results showed that both methods have increased the classification accuracy.     

一种基于CNN-SE-ELM的年龄和性别识别模型

基于人脸图像识别年龄及性别是当前人工智能研究的热点之一。提出一种综合卷积神经网络CNN、挤压-激励网络SENet及极限学习机ELM的混合模型。模型中的卷积层用于从人脸图像中提取面部特征,SENet层用于优化卷积层提取的特征,误差最小化极限学习机（EM-ELM）用作分类器以实现面部图像的年龄及性别识别。与现有的流行模型相比,所提模型由于采用了CNN+SENet架构能够从面部图像中提取到更具代表性及最优的特征映射,而EM-ELM的极速计算使得模型更快速、更高效。在多个非限制人脸数据集上的实验结果表明, 相比近期其他基于深度学习的相关模型,所提模型具有更高的识别准确率和更快的识别速度。     

Theoretical approaches to gender and IT: examining some Australian evidence

Researchers have sought a theoretical perspective to explain the under‐representation of women in the information technology (IT) workforce of many nations. Gender imbalance limits the size and skill sets of IT human resources. The essentialist theory, social construction theory and individual differences theory of gender and IT have been proposed to account for the IT gender gap. This study examined evidence for these theories to explain this gap through content analysis of articles published in the national newspaper, The Australian, over three time periods. Newspaper articles report implicit theoretical perspectives on IT and gender and influence the views of the Australian public, including women. While evidence to support all theories was found over the three periods, the essentialist theory was dominant. Increased utility of the individual differences theory to account for the IT gender gap was seen in 2007–2008. The primary contribution of this study is to provide evidence that suggests that theoretical approaches, whether implicit or explicit, shape how people understand the under‐representation of women in the IT workforce. Media interventions are proposed to help redress the imbalance through increased awareness.     

Gender Differences in Motivations for Identity Reconstruction on Social Network Sites

Social network sites provide people a unique opportunity for self-presentation. Due to various reasons, people may build an online identity that is partly or even completely different from their identity in the real world. Adopting social role theory as the theoretical foundation, the current study investigated gender differences in the motivations for virtual identity reconstruction on QQ, a social network site based in China. A total of 418 respondents participated in the study. As hypothesized, the results showed that men and women are motivated differently when reconstructing their identity – while women focus more on physical vanity, men emphasize achievement vanity. The authors also identified gender differences in other motivations for online identity reconstruction: bridging social capital, disinhibition, and privacy concerns. The results, which suggest that men and women behave in gender-specific ways, are in line with the propositions made in social role theory.