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Crowdsourcing ratings for single lexical items 众包单个词汇的评分
Pub Date : 2022-12-29 DOI: 10.4312/slo2.0.2022.2.5-61
Elena Volodina, David Alfter, Therese Lindström Tiedemann
In this study, we investigate theoretical and practical issues connected to differentiating between core and peripheral vocabulary at different levels of linguistic proficiency using statistical approaches combined with crowdsourcing. We also investigate whether crowdsourcing second language learners’ rankings can be used for assigning levels to unseen vocabulary. The study is performed on Swedish single-word items.The four hypotheses we examine are: (1) there is core vocabulary for each proficiency level, but this is only true until CEFR level B2 (upper-intermediate); (2) core vocabulary shows more systematicity in its behavior and usage, whereas peripheral items have more idiosyncratic behavior; (3) given that we have truly core items (aka anchor items) for each level, we can place any new unseen item in relation to the identified core items by using a series of comparative judgment tasks, this way assigning a “target” level for a previously unseen item; and (4) non-experts will perform on par with experts in a comparative judgment setting. The hypotheses have been largely confirmed: In relation to (1) and (2), our results show that there seems to be some systematicity in core vocabulary for early to mid-levels (A1-B1) while we find less systematicity for higher levels (B2-C1). In relation to (3), we suggest crowdsourcing word rankings using comparative judgment with known anchor words as a method to assign a “target” level to unseen words. With regard to (4), we confirm the previous findings that non-experts, in our case language learners, can be effectively used for the linguistic annotation tasks in a comparative judgment setting.
在本研究中,我们采用统计学方法结合众包的方法,探讨了与区分不同语言熟练程度的核心词汇和外围词汇相关的理论和实践问题。我们还研究了众包第二语言学习者的排名是否可以用于为未见过的词汇分配级别。这项研究是在瑞典语单词项目上进行的。我们检验的四个假设是:(1)每个熟练程度都有核心词汇,但这只适用于CEFR B2(中高级)水平;(2)核心词汇的行为和使用表现出更强的系统性,而外围词汇的行为表现出更强的特质性;(3)鉴于我们在每个关卡中都拥有真正的核心道具(即锚定道具),我们可以通过使用一系列比较判断任务将任何新的未见道具与已识别的核心道具联系起来,从而为之前未见的道具分配“目标”关卡;(4)在比较判断设置中,非专家的表现与专家相当。假设在很大程度上得到了证实:关于(1)和(2),我们的结果表明,在早期到中期水平(A1-B1)的核心词汇中似乎存在一些系统性,而在较高水平(B2-C1)的核心词汇中,我们发现系统性较低。关于(3),我们建议使用与已知锚词比较判断的众包词排名作为一种为未见词分配“目标”级别的方法。关于(4),我们证实了之前的研究结果,即在我们的案例中,语言学习者可以有效地用于比较判断设置中的语言注释任务。
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引用次数: 0
Crowdsourcing and language learning habits and practices in Turkey, Bosnia and Herzegovina, the Republic of North Macedonia and Poland in the pre-pandemic and pandemic periods 大流行前和大流行期间土耳其、波斯尼亚和黑塞哥维那、北马其顿共和国和波兰的众包和语言学习习惯和做法
Pub Date : 2022-12-29 DOI: 10.4312/slo2.0.2022.2.132-183
Çiler Hatipoğlu, Nihada Delibegović Džanić, Elżbieta Gajek, Lina Miloshevska
The popularity of online crowdsourcing platforms was slowly increasing among language learners before the pandemic, but COVID-19 changed the educational systems worldwide. This study aims to uncover whether or not, and if ‘YES’, how the attitudes and habits of language learners concerning the use of crowdsourcing materials in Turkey, Bosnia and Herzegovina, the Republic of North Macedonia and Poland changed during the pandemic. To compare the pre-and during the covid crowdsourcing tool usage, the cross-culturally appropriate questionnaire utilised in the pre-COVID-19 period was used again. The collected data were analysed qualitatively and quantitatively to identify the differences between the periods. The study’s findings showed that the shift from face-to-face to online learning significantly affected the development of crowdsourcing platforms worldwide and their employment in the studied countries. The results also demonstrated that a combination of factors, such as reduced interactions with teachers and peers, an increase in workload, and a lack of support on the part of institutions, led to students taking responsibility for their learning. The number and characteristics of the popular platforms changed from country to country since expectations from students varied.
在大流行之前,在线众包平台在语言学习者中的受欢迎程度正在缓慢上升,但COVID-19改变了全球的教育体系。这项研究的目的是揭示是否,如果“是”,在大流行期间,土耳其、波斯尼亚和黑塞哥维那、北马其顿共和国和波兰的语言学习者对使用众包材料的态度和习惯是如何变化的。为了比较covid -19之前和期间众包工具的使用情况,再次使用了在covid -19之前使用的跨文化合适的问卷。收集的数据进行了定性和定量分析,以确定不同时期之间的差异。研究结果显示,从面对面学习到在线学习的转变显著影响了全球众包平台的发展及其在被研究国家的就业。研究结果还表明,与老师和同学的互动减少、工作量增加以及机构缺乏支持等因素的综合作用导致学生对自己的学习负责。由于学生的期望不同,受欢迎的平台的数量和特征也因国家而异。
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引用次数: 0
Application of crowdsourcing in education on the example of eTwinning 众包在教育中的应用——以ettwin为例
Pub Date : 2022-12-29 DOI: 10.4312/slo2.0.2022.2.184-201
Elżbieta Gajek
While eTwinning is focused on facilitating collaboration among schools in Europe and beyond, the extensive participation of over one million teachers from 44 countries makes the program an extensive educational crowdsourcing activity. In this paper the program which structures the related pedagogical approaches and practices will be analyzed and discussed in light of the crowdsourcing principles. Teachers and students participate in the program voluntarily. All collaborative activities, material production and publication of results which take place online and emphasize language learning fulfil the characteristics of the effective use of crowdsourcing in education. Two kinds of analyses are undertaken, a global analysis of the program features and local analysis of the selected projects. The global analysis relates the crowdsourcing practices to the eTwinning activities. The local analysis is based on the outstanding projects submitted for evaluation for national awards in Poland, further exemplified by activities and reference to the public sites of the projects. The aim of the text is to show that teachers may effectively use crowdsourcing in educational practice even when not primarily focused on its application.
虽然eTwinning的重点是促进欧洲和其他地区学校之间的合作,但来自44个国家的100多万名教师的广泛参与使该计划成为一项广泛的教育众包活动。在本文中,将根据众包原则分析和讨论构建相关教学方法和实践的程序。教师和学生自愿参加该计划。所有在网上进行并强调语言学习的协作活动、材料制作和成果发布都符合在教育中有效利用众包的特点。本文进行了两种分析,一种是对项目特征的全局分析,另一种是对选定项目的局部分析。全球分析将众包实践与eTwinning活动联系起来。本地分析是基于提交波兰国家奖项评估的优秀项目,进一步通过项目的活动和参考公共场所来举例说明。本文的目的是表明,教师可以有效地使用众包在教育实践中,即使不是主要集中在其应用。
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引用次数: 0
Data preparation in crowdsourcing for pedagogical purposes 以教学为目的的众包数据准备
Pub Date : 2022-12-29 DOI: 10.4312/slo2.0.2022.2.62-100
Tanara Zingano Kuhn, Špela Arhar Holdt, Iztok Kosem, Carole Tiberius, Kristina Koppel, R. Zviel-Girshin
One way to stimulate the use of corpora in language education is by making pedagogically appropriate corpora, labeled with different types of problems (sensitive content, offensive language, structural problems). However, manually labeling corpora is extremely time-consuming and a better approach should be found. We thus propose a combination of two approaches to the creation of problem-labeled pedagogical corpora of Dutch, Estonian, Slovene and Brazilian Portuguese: the use of games with a purpose and of crowdsourcing for the task. We conducted initial experiments to establish the suitability of the crowdsourcing task, and used the lessons learned to design the Crowdsourcing for Language Learning (CrowLL) game in which players identify problematic sentences, classify them, and indicate problematic excerpts. The focus of this paper is on data preparation, given the crucial role that such a stage plays in any crowdsourcing project dealing with the creation of language learning resources. We present the methodology for data preparation, offering a detailed presentation of source corpora selection, pedagogically oriented GDEX configurations, and the creation of lemma lists, with a special focus on common and language-dependent decisions. Finally, we offer a discussion of the challenges that emerged and the solutions that have been implemented so far.
促进语料库在语言教育中的使用的一种方法是制作适合教学的语料库,标记不同类型的问题(敏感内容、攻击性语言、结构性问题)。然而,手动标注语料库是非常耗时的,应该找到更好的方法。因此,我们建议结合两种方法来创建荷兰语、爱沙尼亚语、斯洛文尼亚语和巴西葡萄牙语的问题标记教学语料库:使用有目的的游戏和众包来完成任务。我们进行了初步实验,以确定众包任务的适用性,并利用吸取的经验教训设计了语言学习众包(CrowLL)游戏,让玩家识别问题句子,对它们进行分类,并指出问题摘录。本文的重点是数据准备,因为这一阶段在任何涉及语言学习资源创建的众包项目中都起着至关重要的作用。我们介绍了数据准备的方法,详细介绍了源语料库的选择、以教学为导向的GDEX配置和引理列表的创建,并特别关注公共和语言相关的决策。最后,我们将讨论到目前为止出现的挑战和已经实施的解决方案。
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引用次数: 0
EnetCollect – European Network for Combining Language Learning with Crowdsourcing Techniques (COST Action CA16105) EnetCollect -结合语言学习和众包技术的欧洲网络(成本行动CA16105)
Pub Date : 2022-12-29 DOI: 10.4312/slo2.0.2022.2.202-225
Lionel Nicolas, V. Lyding
This article reviews the European Network for Combining Language Learning with Crowdsourcing Techniques (enetCollect), an extensive network project created to foster research and innovation (R&I) on the combination of crowdsourcing and language learning. Accordingly, we explain how it began, introduce its overall logic and organization, and discuss its achievements in terms of both (1) creating a new R&I community through a concluded large network project, and (2) fostering R&I on a high-potential and mostly unexplored subject.We also discuss the challenges involved and lessons learned, whether in orchestrating and leading a new R&I community or the challenges we faced and generally observed in the efforts of enetCollect members, as they explored the many facets of such a versatile enterprise.
本文回顾了欧洲语言学习与众包技术结合网络(enetCollect),这是一个广泛的网络项目,旨在促进众包和语言学习结合的研究和创新(R&I)。因此,我们解释了它是如何开始的,介绍了它的整体逻辑和组织,并从以下两个方面讨论了它的成就:(1)通过一个结束的大型网络项目创建一个新的R&I社区,以及(2)在一个高潜力和大部分未开发的主题上培养R&I。我们还讨论了所涉及的挑战和经验教训,无论是在组织和领导一个新的R&I社区方面,还是在enetCollect成员探索这样一个多功能企业的许多方面时,我们所面临的挑战和通常观察到的挑战。
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引用次数: 0
Learning languages from parallel corpora 从平行语料库中学习语言
Pub Date : 2022-12-29 DOI: 10.4312/slo2.0.2022.2.101-131
Johannes Graën
This work describes a blueprint for an application that generates language learning exercises from parallel corpora. Word alignment and parallel structures allow for the automatic assessment of sentence pairs in the source and target languages, while users of the application continuously improve the quality of the data with their interactions, thus crowdsourcing parallel language learning material. Through triangulation, their assessment can be transferred to language pairs other than the original ones if multiparallel corpora are used as a source.Several challenges need to be addressed for such an application to work, and we will discuss three of them here. First, the question of how adequate learning material can be identified in corpora has received some attention in the last decade, and we will detail what the structure of parallel corpora implies for that selection. Secondly, we will consider which type of exercises can be generated automatically from parallel corpora such that they foster learning and keep learners motivated. And thirdly, we will highlight the potential of employing users, that is both teachers and learners, as crowdsourcers to help improve the material.
这项工作描述了一个从平行语料库生成语言学习练习的应用程序的蓝图。单词对齐和并行结构允许自动评估源语言和目标语言的句子对,而应用程序的用户通过他们的交互不断提高数据的质量,从而众包并行语言学习材料。如果以多平行语料库为源,通过三角测量可以将其评价转移到原始语言对以外的语言对上。要使这样的应用程序工作,需要解决几个挑战,我们将在这里讨论其中的三个挑战。首先,如何在语料库中识别足够的学习材料的问题在过去十年中受到了一些关注,我们将详细介绍平行语料库的结构对这种选择意味着什么。其次,我们将考虑哪些类型的练习可以从平行语料库中自动生成,从而促进学习并保持学习者的动力。第三,我们将强调雇用用户的潜力,即教师和学习者,作为众包者来帮助改进材料。
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引用次数: 0
Crowdsourcing for language learning and linguistic resource creation 语言学习和语言资源创造的众包
Pub Date : 2022-12-29 DOI: 10.4312/slo2.0.2022.2.1-4
Lionel Nicolas, V. Lyding
The current special issue of the journal Slovenščina 2.0 focuses on the newly explored combination of crowdsourcing, language learning and linguistic resource creation. It contains five articles and one project report, providing insightful discussions on several aspects of this combination, as well as results which help us understand its versatile potential and the challenges to address in order to better exploit it.
目前的期刊Slovenščina 2.0特刊重点关注众包、语言学习和语言资源创造的新探索组合。它包含五篇文章和一份项目报告,对这一组合的几个方面提供了深刻的讨论,以及帮助我们了解其多功能潜力和为了更好地利用它而需要解决的挑战的结果。
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引用次数: 0
Konferenca Jezikovne tehnologije in digitalna humanistika 2022
Pub Date : 2022-12-21 DOI: 10.4312/slo2.0.2022.1.131-135
David Bordon
Poročilo s konference Jezikovne tehnologije in digitalna humanistika (JTDH) 2022, ki je potekala septembra 2022 v prostorih Fakultete za družbene vede Univerze v Ljubljani. Konferenco je priredilo Slovensko društvo za jezikovne tehnologije (SDJT), v soorganizaciji s Centrom za jezikovne vire in tehnologije Univerze v Ljubljani (CJVT), Inštitutom za novejšo zgodovino (INZ) ter raziskovalnima infrastrukturama CLARIN.SI in DARIAH-SI.
2022 年语言技术与数字人文会议 (JTDH) 报告,会议于 2022 年 9 月在卢布尔雅那大学社会科学学院举行。会议由斯洛文尼亚语言技术协会(SDJT)主办,卢布尔雅那大学语言资源与技术中心(CJVT)、当代历史研究所(INZ)以及研究基础设施 CLARIN.SI 和 DARIAH-SI 协办。
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引用次数: 0
33. evropska poletna šola logike, jezika in informatike ESSLLI 2022
Pub Date : 2022-12-21 DOI: 10.4312/slo2.0.2022.1.126-130
M. Brglez
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引用次数: 0
Emotion analysis in socially unacceptable discourse 社会不可接受话语中的情感分析
Pub Date : 2022-12-21 DOI: 10.4312/slo2.0.2022.1.1-22
Jasmin Franza, Bojan Evkoski, Darja Fišer
Texts often express the writer’s emotional state, and it was shown that emotion information has potential for hate speech detection and analysis. In this work, we present a methodology for quantitative analysis of emotion in text. We define a simple, yet effective metric for an overall emotional charge of text based on the NRC Emotion Lexicon and Plutchik’s eight basic emotions. Using this methodology, we investigate the emotional charge of content with socially unacceptable discourse (SUD), as a distinct and potentially harmful type of text which is spreading on social media. We experiment with the proposed method on a corpus of Facebook comments, resulting in four datasets in two languages, namely English and Slovene, and two discussion topics, LGBT+ rights, and the European Migrants crisis. We reveal that SUD content is significantly more emotional than non-SUD comments. Moreover, we show differences in the expression of emotions depending on the language, topic, and target of the comments. Finally, to underpin the findings of the quantitative investigation of emotions, we perform a qualitative analysis of the corpus, exploring in more detail the most frequent emotional words of each emotion, for all four datasets. The qualitative analysis shows that the source of emotions in SUD texts heavily depends on the topic of discussion, with substantial overlaps between languages.
文本往往表达了作者的情绪状态,研究表明情绪信息具有检测和分析仇恨言论的潜力。在这项工作中,我们提出了一种定量分析文本情感的方法。我们基于NRC情感词典和Plutchik的八种基本情感定义了一个简单而有效的文本整体情感负荷度量。使用这种方法,我们研究了社会不可接受话语(SUD)内容的情感负荷,作为一种独特的、潜在有害的文本类型,正在社交媒体上传播。我们在一个Facebook评论语料库上对提出的方法进行了实验,得到了英语和斯洛文尼亚语两种语言的四个数据集,以及两个讨论主题,LGBT+权利和欧洲移民危机。我们发现,南德意志的内容明显比非南德意志的评论更情绪化。此外,根据评论的语言、话题和目标,我们显示了情感表达的差异。最后,为了支持情绪定量调查的发现,我们对语料库进行了定性分析,更详细地探索了所有四个数据集中每种情绪中最常见的情感词汇。定性分析表明,SUD文本中情绪的来源在很大程度上取决于讨论的主题,语言之间存在大量重叠。
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引用次数: 2
期刊
Slovenščina 2.0: empirical, applied and interdisciplinary research
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