Social Rights and Work on Digital Platforms in Brazil:The Case of“Breque dos Apps”

The movement known as“Breque dos Apps”was a social movement of a striker nature,which took place in Brazil in July 2020.Such movement was organized by workers which provided services to delivery apps(like iFood,Loggi,Uber Eats and Rappi).They demanded better working conditions and social protection measures,since they were out of the protection of the Brazilian legal system.The reason for this lies in the fact that there is a debate about the classification of these workers-the maximum expression of the gig economy-as employees under Brazilian legislation.As a result,and with the exponential growth in the use of these applications due to the Covid-19 pandemic,thousands of workers were left on the fringes of any social protection.This study aims to analyze the aforementioned movement and its demands within the paradigm of social rights,especially the ones regarding collective representation,which are guaranteed by the Brazilian Constitution.In terms of methodology,the content analysis method will be applied,considering that the established objective presupposes the study of theoretical and legal texts that allow the structuring of concepts applicable to the theme.The research technique to be adopted will be the analysis of indirect documentation,that is,literature review,to be carried out through bibliographic and documentary research,focused on literature and legal texts related to the topic.

Thalassemia Screening by Sentiment Analysis on Social Media Platform Twitter

Thalassemia syndrome is a genetic blood disorder induced by the reduction of normal hemoglobin production,resulting in a drop in the size of red blood cells.In severe forms,it can lead to death.This genetic disorder has posed a major burden on public health wherein patients with severe thalassemia need periodic therapy of iron chelation and blood transfusion for survival.Therefore,controlling thalassemia is extremely important and is made by promoting screening to the general population,particularly among thalassemia carriers.Today Twitter is one of the most influential social media platforms for sharing opinions and discussing different topics like people’s health conditions and major public health affairs.Exploring individuals’sentiments in these tweets helps the research centers to formulate strategies to promote thalassemia screening to the public.An effective Lexiconbased approach has been introduced in this study by highlighting a classifier called valence aware dictionary for sentiment reasoning(VADER).In this study applied twitter intelligence tool(TWINT),Natural Language Toolkit(NLTK),and VADER constitute the three main tools.VADER represents a gold-standard sentiment lexicon,which is basically tailored to attitudes that are communicated by using social media.The contribution of this study is to introduce an effective Lexicon-based approach by highlighting a classifier calledVADERto analyze the sentiment of the general population,particularly among thalassemia carriers on the social media platform Twitter.In this study,the results showed that the proposed approach achieved 0.829,0.816,and 0.818 regarding precision,recall,together with F-score,respectively.The tweets were crawled using the search keywords,“thalassemia screening,”thalassemia test,“and thalassemia diagnosis”.Finally,results showed that India and Pakistan ranked the highest in mentions in tweets by the public’s conversations on thalassemia screening with 181 and 164 tweets,respectively.

Does communication increase investors’trading frequency?Evidence from a Chinese social trading platform

This study examines the impact of communication on investors’trading frequency based on a unique dataset drawn from a Chinese social trading platform.We find robust evidence that real-account portfolio owners on the platform trade more frequently under the influence of the comments posted by their leaders(the owners of portfolios they have followed).Moreover,portfolio owners are more sensitive to the quantity than to the tone of leaders’comments.Finally,both trading frequency and leaders’comments negatively impact portfolio owners’future performance.Our find-ings support the notion that social interaction promotes active investment strategies.

UPLC-Q-TOF-MS^(E)技术结合UNIFI筛查平台分析加味逍遥丸化学成分

目的运用高效液相色谱-四极杆-飞行时间串联质谱法(UPLC-Q-TOF-MS^(E))对加味逍遥丸的化学成分进行分析与鉴定,为复方质量控制及药效物质基础研究提供理论依据。方法采用ACQUITY UPLC BEH C_(18)柱(2.1 mm×100 mm,1.7μm,Waters),以0.1%甲酸水-乙腈为流动相,梯度洗脱,进样量5μL,流速0.3 mL·min^(-1),柱温40℃。采用电喷雾离子源,在正、负2种模式下进行复方质谱检测与分析,并且使用UNIFI平台对MS^(E)模式下采集的质谱数据,结合化合物准分子离子、质谱裂解途径及标准品进行结构确认。结果通过分析目标化合物的分子离子峰和二级质谱特征碎片离子,并且结合标准品裂解规律以及相关文献资料,共鉴定了其中78个化学成分,包括3个倍半萜类成分、4个苯丙素类成分、13个单萜类成分、7个酚类成分、5个环烯醚萜类成分、10个黄酮类成分、23个三萜类成分及13个其他类成分。结论运用UPLC-Q-TOF-MS^(E)技术可快速分析鉴定复方加味逍遥丸的主要化合物类型,可为复方质量控制及药效物质基础研究提供理论依据。

Cyber-Physical-Social System Between a Humanoid Robot and a Virtual Human Through a Shared Platform for Adaptive Agent Ecology

Two artificial agents(a humanoid robot and a virtual human) are enriched with various similar intelligence,autonomy, functionalities and interaction modalities. The agents are integrated in the form of a cyber-physical-social system(CPSS) through a shared communication platform to create a social ecology. In the ecology, the agents collaborate(assist each other) to perform a real-world task(search for a hidden object)for the benefits of humans. A robot-virtual human bilateral trust model is derived and a real-time trust measurement method is developed. The role of taking initiative in the collaboration is switched between the agents following a finite state machine model triggered by bilateral trust, which results in a mixedinitiative collaboration. A scheme is developed to evaluate the performance of the agents in the ecology through the CPSS.The results show that the robot and the virtual human perform satisfactorily in the collaboration through the CPSS. The results thus prove the effectiveness of the real-world ecology between artificial agents of heterogeneous realities through a shared platform based on trust-triggered mixed-initiatives. The results can help develop adaptive social ecology comprising intelligent agents of heterogeneous realities to assist humans in various tasks through collaboration between the agents in the form of a CPSS.

基于iQ Platform平台的三菱多机器人协作工作站的建立

本文构建了一种基于三菱公司iQ Platform平台,由两台三菱RV-2FR-Q机器人、CR800-Q2VQ、Q03UDECPU、Q172DSRCPU、QX40、QY10和TPC7200K触摸屏组成的多机器人协作工作站。

Online Social Skills Group Training for Adolescents and Young Adults with 22q11.2 Deletion Syndrome (22q11.2DS)

Somatic, cognitive and psychiatric obstacles contribute to social impairment in 22q11.2DS and prevent adequate responses during interactions. We adapted the autism-specific SOSTA-FRA program for use during online group sessions with geographically-isolated 22q11DS adolescents or adults. The 12 weekly sessions targeted communication, emotional awareness, and reciprocity. Twenty-two participants were evaluated on behaviour, social responsiveness, and cognition pre- and post-intervention. Parents completed a questionnaire to ascertain whether the intervention met their needs. Parents were satisfied with the format and curriculum contents and reported improved emotional awareness, well-being, and reciprocity post-intervention. Pre-post results suggest large effects on social awareness and small to medium effects on social motivation. Results indicate that online social skills training is feasible and effective for individuals with 22q11.2DS.

The Development and Operation Mechanism of the Colleges’E-class Network Ideological and Political Education Platform——Based on post-95 college students’social behavior characteristics

Based on the investigation and analysis of the social behavior characteristics of post-95undergraduates, this paper puts forward the principle of sharing and building e-class platform and analyzes thedevelopment of the functions of the four platforms such as the teacher-student service system, instant interactionsystem, SNS community system and vertical segmental pushing system and the realization of the function of modularoperation. Finally, in order to ensure the stable operation of the E-class platform, four measures are put forward suchas the systematic construction of the system, the innovation of team work, the assessment of key performances and thecomprehensive guarantee, thus providing an external guarantee for the stable operation of the E-class platform.

Multimodal sentiment analysis for social media contents during public emergencies

Purpose:Nowadays,public opinions during public emergencies involve not only textual contents but also contain images.However,the existing works mainly focus on textual contents and they do not provide a satisfactory accuracy of sentiment analysis,lacking the combination of multimodal contents.In this paper,we propose to combine texts and images generated in the social media to perform sentiment analysis.Design/methodology/approach:We propose a Deep Multimodal Fusion Model(DMFM),which combines textual and visual sentiment analysis.We first train word2vec model on a large-scale public emergency corpus to obtain semantic-rich word vectors as the input of textual sentiment analysis.BiLSTM is employed to generate encoded textual embeddings.To fully excavate visual information from images,a modified pretrained VGG16-based sentiment analysis network is used with the best-performed fine-tuning strategy.A multimodal fusion method is implemented to fuse textual and visual embeddings completely,producing predicted labels.Findings:We performed extensive experiments on Weibo and Twitter public emergency datasets,to evaluate the performance of our proposed model.Experimental results demonstrate that the DMFM provides higher accuracy compared with baseline models.The introduction of images can boost the performance of sentiment analysis during public emergencies.Research limitations:In the future,we will test our model in a wider dataset.We will also consider a better way to learn the multimodal fusion information.Practical implications:We build an efficient multimodal sentiment analysis model for the social media contents during public emergencies.Originality/value:We consider the images posted by online users during public emergencies on social platforms.The proposed method can present a novel scope for sentiment analysis during public emergencies and provide the decision support for the government when formulating policies in public emergencies.

Cyber Development of Government Service Platform in Social Public Administration

The cyber development of government service platform is just to integrate all the superiorities of the government to strengthen its roles such as service,performance and function to drive the social development actively.Hence,the social public administration will take this opportunity to optimize the cyber information service platform to make the civic administration oriented to the social development to maximize its functions of organization,coordination and service to protrude the ascendancy of the web era so as to lay a solid foundation for the leap development of the public administration.

社交商务平台的同质性、茧房效应及破解策略研究

社交商务作为数字经济的重要组成,拥有巨大的市场潜力,但也面临着平台发展模式同质化等问题,导致形成固化用户的自我认识和网络信息行为的信息茧房。由于社交媒体的多样性、群体关系复杂性,茧房效应与社交商务结合的研究有待进一步挖掘。通过中国知网和Web of Science核心集,截至2023年3月31日,检索并筛选获取606篇相关文献,运用社会网络分析方法进行分析。其中300篇中文文献重点探讨个性化推荐算法对信息茧房形成的影响,306篇英文文献更多关注信息茧房与平台和用户行为之间的关系。基于信息茧房相关概念的研究明确其内涵和特征,根据平台、算法和用户3个维度的作用机制分析构建信息同质化视角下信息茧房形成机制框架,即社交平台内外部信息趋同导致了用户选择同质化、平台内容同质化以及用户群体同质化问题,并以正反馈的形式不断加强,最终形成信息茧房。由此,基于同质化视角,分别从政府、平台和用户3个主体层面提出社交商务平台应对信息茧房的策略。

人机交互场景下用户知识吸收能力影响因素的组态分析

基于社会认知理论,采用模糊集定性比较分析(fsQCA)方法,探讨在人机交互场景下,平台环境和个体认知如何互动影响平台用户的知识吸收能力。研究发现:环境因素是人机互动知识共享的基础,而与个体认知因素相匹配的交互设计是提升吸收效能的关键。促进强吸收能力形成的核心条件有强联结、高信任的环境因素和强自我效能和高结果期望的认知因素;导致吸收能力弱的核心条件则是用户之间过大的知识距离和过弱的联结强度等环境因素。研究结论为知识平台提升用户知识吸收能力提供了理论依据与现实启示,为未来提升人机交互设计促进知识共享的研究提供参考借鉴。

平台型企业的社会责任治理能提升用户响应吗?——基于短视频平台的调查研究

随着平台经济的崛起,平台型企业已成为社会经济发展的主力军,平台型企业的社会责任治理备受瞩目。基于SOR模型构建了平台型企业社会责任治理、用户内部心理响应与用户外部行为响应之间的理论模型,以短视频平台为研究对象,采用问卷调查法收集数据进行实证检验。研究发现:无论是对用户内部心理响应(满意度和认同度),还是对用户外部行为响应(持续使用意愿和社会责任参与意愿),贡献责任治理、合理责任治理和底线责任治理呈现出了由强到弱的正向影响程度,体现了3种责任的内涵和本质差异。并且,3种责任治理对认同度的影响均强于对满意度的影响,认同度对外部行为响应的影响也强于满意度对其的影响,揭示出反映长期心理承诺的认同度,相比反映短期心理认知的满意度,是更为关键的内部心理响应变量。另外,用户粘性能正向调节合理责任治理、贡献责任治理和社会责任参与意愿之间的关系。

基于SEM与ANN混合方法的社交问答平台用户转移行为

社交问答平台得到了用户的广泛使用,但由于各平台的功能类似,用户转移起来较为容易,这将导致用户流失。基于PPM模型,研究社交问答平台用户转移行为。采集447份有效数据,采用SEM(结构方程模型)与ANN(人工神经网络)混合方法进行分析。结果发现:推力因素(不满意度、厌倦性)和拉力因素(内容质量、用户体验)正向影响用户的转移意向,锚定因素(转移成本)负向影响转移意向,且负向调节推力因素和拉力因素的作用。ANN结果显示:不满意度是影响转移意向的最重要因素。因此,社交问答平台需要提高内容质量,改善用户体验,降低用户的不满意度和厌倦性,从而防止用户的转移行为,实现用户保持。

企业社交媒体平台印象管理策略——基于新浪微博数据的内容分析

互联网时代,企业使用社交媒体平台进行印象管理能够改变受众认知,树立良好的企业形象。探讨企业在社交媒体平台上印象管理策略分类,利用数据爬虫软件搜集新浪微博品牌排行榜前10名的企业微博推文,通过内容分析法得出企业在社交媒体平台上经常使用的具体策略有四种:自我呈现、企业社会责任、道歉声明、辩解对抗。此外,还发现企业在道歉声明中还会结合自我呈现或者辩解进行策略地组合应用。

预付式消费政府平台法律监管的治理路径

为应对预付式消费给传统监管体系提出的挑战,一些地方政府利用信息化、互联化的优势,探索建立统一的互联网监管平台。这些平台存在着备案参与度低、平台风险警示制度缺乏互联互通等困境,究其根源是由于政府管控型监管理念与风险预防逻辑不适应;监管权力配置模式过于僵化;制度规范滞后于监管需求;监管工具的创新性不足。为治理上述困境,亟需从政府管控监管理念转换为多元协同监管理念;构建“部门协同、社会共担”的监管权力配置格局;健全“风险预防、程序保障”为导向的监管规范体系;创新监管工具以提高风险预防的精准性等四个方面的改革路径,为治理政府主导型预付式消费互联网平台的监管困境提供思路。

“平台”与我国县域基层法治秩序的生成——浙江海宁社会治理实践的观察

基层社会治理“平台”是我国县域范围构建具有中国特色法治秩序的重要实践形式。在提升县域基层社会治理水平的过程中,平台被打造成一个由不同政府机构、不同社会组织与社会成员通过协调、协商、议论等方式博弈以解决与民生密切相关的各种类型问题的工作机制,客观上已经助力生成了法治秩序不可或缺的不同主体之间展开话语交流的公共空间。在浙江海宁,平台被用于促进实现公众与企业合法权利、改造和规范行使公共权力、保障社会稳定与居民安居乐业,以公开促公正公平,有效提升了法律在基层的实施能力。在法治建设正在寻求新的突破之际,有关平台建设的实践具有一定的可借鉴的普遍意义。

平台特征对跨社交媒体UGC信息分享行为的影响机理研究

[目的/意义]探究平台特征对跨社交媒体UGC信息分享行为的影响,揭示用户跨社交媒体场景的新特征。[方法/过程]通过刺激—机体—反应(SOR)理论框架构建平台特征对跨社交媒体UGC信息分享行为的中介调节模型,以时间维度和平台维度拼接应用商城数据、百度指数数据、社交媒体数据等,构建多源异构面板数据集作为样本,使用固定效应模型验证相关假设。[结果/结论]平台的声誉和用户服务技术迭代通过感知有用性正向影响跨社交媒体UGC信息分享,而平台的关注度通过感知有用性显著负向影响信息分享行为;平台声誉和用户服务技术迭代对感知有用性和跨社交媒体UGC信息分享之间的关系具有负向调节作用。本文关注跨社交媒体UGC的信息分享行为,为UGC创作者采用跨社交媒体信息投放策略提供参照,为社交媒体维护平台生态提供启示。

基于神经网络词嵌入的大数据关注热点和词嵌入概貌比较研究

[目的/意义]大数据对社会和经济发展产生了重大影响,本研究结合我国学术平台和社会化问答平台对大数据关注热点和词嵌入概貌进行比较,旨在推动我国大数据研究和实践。[方法/过程]Word2vec是新兴的神经网络词嵌入算法,具有计算成本低、准确度高等特点,能够同时在语义层面和语法层面有效测度词语的相似度。首先,结合中国知网和知乎平台分别搜集了数据,构建出学术平台和社会化问答平台的语料库,再基于这两个语料库分别训练了Word2vec模型;其次,结合最相似词语分析对学术平台和社会化问答平台的大数据关注热点进行了比较;最后,利用降维技术和数据可视化方法对两个平台词语的词嵌入概貌进行了比较。[结果/结论]研究结果显示了我国学术平台和社会化问答平台在大数据方面的差异。本研究创新地利用Word2vec神经网络词嵌入算法,结合我国学术平台和社会化问答平台对大数据进行了比较分析,为大数据研究提供了新的视角。

基于Aki模型的近震S波尾波Q值求解及分析软件研制

介绍了基于Ak i单次散射模型,在M atlab平台下开发研制近震S波尾波Q值的求解及分析软件的相关思路及数据实现、资料处理过程、窗口化程序软件模块的功能及使用方法,定量计算并分析了噪声水平、滤声器性能、数据采样等因素对计算尾波Q值的影响,数据处理中引入了数据的动态采样方法。为了便于使用,该软件在设计上即设置了相关计算的默认控制参数,同时又对一些关键控制参数预留了可输入数据接口。