协同标记

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模板:Distinguish Folksonomy is a classification system in which end users apply public tags to online items, typically to make those items easier for themselves or others to find later. Over time, this can give rise to a classification system based on those tags and how often they are applied or searched for, in contrast to a taxonomic classification designed by the owners of the content and specified when it is published.[1][2] This practice is also known as collaborative tagging,[3][4] social classification, social indexing, and social tagging. Folksonomy was originally "the result of personal free tagging of information [...] for one's own retrieval",[5] but online sharing and interaction expanded it into collaborative forms. Social tagging is the application of tags in an open online environment where the tags of other users are available to others. Collaborative tagging (also known as group tagging) is tagging performed by a group of users. This type of folksonomy is commonly used in cooperative and collaborative projects such as research, content repositories, and social bookmarking.


Folksonomy is a classification system in which end users apply public tags to online items, typically to make those items easier for themselves or others to find later. Over time, this can give rise to a classification system based on those tags and how often they are applied or searched for, in contrast to a taxonomic classification designed by the owners of the content and specified when it is published. (isabella-peters.de) This practice is also known as collaborative tagging, social classification, social indexing, and social tagging. Folksonomy was originally "the result of personal free tagging of information [...] for one's own retrieval", but online sharing and interaction expanded it into collaborative forms. Social tagging is the application of tags in an open online environment where the tags of other users are available to others. Collaborative tagging (also known as group tagging) is tagging performed by a group of users. This type of folksonomy is commonly used in cooperative and collaborative projects such as research, content repositories, and social bookmarking.

协同标记是一个允许最终用户将大众化的标签应用到网络条目的分类系统。与那些在发布的时候该系统通常能够使对应的网络条目更加容易被用户自己或其他用户检索到。随着时间的推移，与那些在发布时就被设计者定义好分类方式的方法相比，基于大众化标协同标记和它们被应用或搜索的频率，就可以产生一个分类方式。这种做法也被称为合作化标签、社会化分类，社会化索引或社会化标签。协同标记最初是个人为了方便信息的再次查找为信息设置的标签，但是线上共享与互动将它扩展为协作的方式。社会化标签是在一个开放的在线环境中应用标签，一些用户的标签对另外的用户是可用的。合作化标签(也称为组标签)是由一组用户执行的标签。这种类型的协同标记通常用于合作和协作项目，如研究、内容库和社会性书签。

The term was coined by Thomas Vander Wal in 2004[5][6][7] as a portmanteau of folk and taxonomy. Folksonomies became popular as part of social software applications such as social bookmarking and photograph annotation that enable users to collectively classify and find information via shared tags. Some websites include tag clouds as a way to visualize tags in a folksonomy.[8]

The term was coined by Thomas Vander Wal in 2004Vander Wal, T. (2005). "Off the Top: Folksonomy Entries." Visited November 5, 2005. See also: Smith, Gene. "Atomiq: Folksonomy: social classification." Aug 3, 2004. Retrieved January 1, 2007.Origin of the term as a portmanteau of folk and taxonomy. Folksonomies became popular as part of social software applications such as social bookmarking and photograph annotation that enable users to collectively classify and find information via shared tags. Some websites include tag clouds as a way to visualize tags in a folksonomy.

这个术语以民间和分类学的合成词的起源，由 Thomas Vander Wal 在2004年提出。作为能够时用户通过共享标签对信息进行集体分类和查找的社交软件应用（如社会性书签、照片注释）的一部分，协同标记变得流行起来。一些网站将标签云作为一种可视化协同标记中标签的方式。

Folksonomies can be used for K-12 education, business, and higher education. More specifically, folksonomies may be implemented for social bookmarking, teacher resource repositories, e-learning systems, collaborative learning, collaborative research, professional development and teaching. Wikipedia is also a prime example of folksonomy.[9]模板:Better source needed模板:Clarify

Folksonomies can be used for K-12 education, business, and higher education. More specifically, folksonomies may be implemented for social bookmarking, teacher resource repositories, e-learning systems, collaborative learning, collaborative research, professional development and teaching. Wikipedia is also a prime example of folksonomy.

协同标记可用于 K-12教育、商业和高等教育。更具体地说，协同标记可以应用于社会性书签、教师资源库、电子学习系统、合作学习、协作研究、专业发展和教学。维基百科也是协同标记的一个典型例子。

优缺点

Folksonomies are a trade-off between traditional centralized classification and no classification at all,[10] and have several advantages:[11][12][13]

  • Tagging is easy to understand and do, even without training and previous knowledge in classification or indexing
  • The vocabulary in a folksonomy directly reflects the user's vocabulary
  • Folksonomies are flexible, in the sense that the user can add or remove tags
  • Tags consist of both popular content and long-tail content, enabling users to browse and discover new content even in narrow topics
  • Tags reflect the user's conceptual model without cultural, social, or political bias
  • Enable the creation of communities, in the sense that users who apply the same tag have a common interest
  • Folksonomies are multi-dimensional, in the sense that users can assign any number and combination of tags to express a concept

Folksonomies are a trade-off between traditional centralized classification and no classification at all,Gupta, M., et al., An Overview of Social Tagging and Applications, in Social Network Data Analytics, C.C. Aggarwal, Editor. 2011, Springer. p. 447-497. and have several advantages:Quintarelli, E., Folksonomies: power to the people. 2005.Mathes, A., Folksonomies - Cooperative Classification and Communication Through Shared Metadata. 2004.Wal, T.V. Folksonomy. 2007

  • Tagging is easy to understand and do, even without training and previous knowledge in classification or indexing
  • The vocabulary in a folksonomy directly reflects the user's vocabulary
  • Folksonomies are flexible, in the sense that the user can add or remove tags
  • Tags consist of both popular content and long-tail content, enabling users to browse and discover new content even in narrow topics
  • Tags reflect the user's conceptual model without cultural, social, or political bias
  • Enable the creation of communities, in the sense that users who apply the same tag have a common interest
  • Folksonomies are multi-dimensional, in the sense that users can assign any number and combination of tags to express a concept

大众分类是在传统的集中分类和根本没有分类之间的权衡，有以下几个优点：

  • 即使没有经过培训和在先的分类或索引的知识，标签也很容易理解和使用
  • 协同标记的词汇直接反映用户的词汇
  • 协同标记是灵活的，也就是说用户可以添加或删除标签
  • 标签包括流行内容和长尾内容，使用户即使是在狭窄的主题，也能够浏览和发现新的内容，
  • 能够不带有文化，社会或政治偏见的反映用户的概念模型
  • 创建社区，也就是说使用相同标签的用户具有共同的兴趣
  • 协同标记是多维的，也就是说用户可以指定任何数字和组合的标签来表达一个概念

There are several disadvantages with the use of tags and folksonomies as well,[14] and some of the advantages (see above) can lead to problems. For example, the simplicity in tagging can result in poorly applied tags.[15] Further, while controlled vocabularies are exclusionary by nature,[16] tags are often ambiguous and overly personalized.[17] Users apply tags to documents in many different ways and tagging systems also often lack mechanisms for handling synonyms, acronyms and homonyms, and they also often lack mechanisms for handling spelling variations such as misspellings, singular/plural form, conjugated and compound words. Some tagging systems do not support tags consisting of multiple words, resulting in tags like "viewfrommywindow". Sometimes users choose specialized tags or tags without meaning to others.

There are several disadvantages with the use of tags and folksonomies as well,Kipp, M. and D.G. Campbell, Patterns and Inconsistencies in Collaborative Tagging Systems: An Examination of Tagging Practices. Proceedings Annual General Meeting of the American Society for Information Science and Technology, 2006. and some of the advantages (see above) can lead to problems. For example, the simplicity in tagging can result in poorly applied tags.Hayman, S., Folksonomies and Tagging: New developments in social bookmarking, in Proceedings of Ark Group Conference: Developing and Improving Classification Schemes, 2007, Sydney. 2007: Sydney. Further, while controlled vocabularies are exclusionary by nature,Kroski, E., The Hive Mind: Folksonomies and User-Based Tagging. 2005 tags are often ambiguous and overly personalized.Guy, M. and E. Tonkin, Folksonomies: Tidying up Tags? D-Lib Magazine, 2006. 12(Number 1): p. 1-15. Users apply tags to documents in many different ways and tagging systems also often lack mechanisms for handling synonyms, acronyms and homonyms, and they also often lack mechanisms for handling spelling variations such as misspellings, singular/plural form, conjugated and compound words. Some tagging systems do not support tags consisting of multiple words, resulting in tags like "viewfrommywindow". Sometimes users choose specialized tags or tags without meaning to others.

使用标签和协同标记也有几个缺点，而且上文的一些优点也可能带来一些问题。例如，标签的简单性可能导致标签应用不当。此外，虽然受控词汇天生具有排他性，但是标签经常是模棱两可且个性化的。用户以许多不同的方式对文档使用标记，这些标记系统也常常缺乏处理同义词、首字母缩略词和同音词的机制，而且他们还常常缺乏处理拼写错误、单复数形式、共轭词和复合词等拼写变化的机制。一些标签系统不支持由多个单词组成的标签，导致了像“ viewfrommywindow”这样的标签。有时候用户会选择专门的或对其他人来说毫无意义的标签。

基本要素与类型

A folksonomy emerges when users tag content or information, such as web pages, photos, videos, podcasts, tweets, scientific papers and others. Strohmaier et al.[18] elaborate the concept: the term "tagging" refers to a "voluntary activity of users who are annotating resources with term-so-called 'tags' – freely chosen from an unbounded and uncontrolled vocabulary". Others explain tags as an unstructured textual label[19] or keywords,[20] and that they appear as a simple form of metadata.[21]

A folksonomy emerges when users tag content or information, such as web pages, photos, videos, podcasts, tweets, scientific papers and others. Strohmaier et al.Strohmaier, M., C. Körner, and R. Kern, Understanding why users tag: A survey of tagging motivation literature and results from an empirical study. Web Semantics: Science, Services and Agents on the World Wide Web, 2012. 17: p. 1-11. elaborate the concept: the term "tagging" refers to a "voluntary activity of users who are annotating resources with term-so-called 'tags' – freely chosen from an unbounded and uncontrolled vocabulary". Others explain tags as an unstructured textual labelAmes, M.N.M., Why We Tag: Motivations for Annotation in Mobile and Online Media, in SIGCHI conference on Human factors in computing systems. 2007, ACM Press: New York, NY, USA. p. 971-980. or keywords,Guy, M. and E. Tonkin, Folksonomies: Tidying up Tags? D-Lib Magazine, 2006. 12(Number 1): p. 1-15. and that they appear as a simple form of metadata.Brooks, C.H. and N. Montanez, Improved annotation of the blogosphere via autotagging and hierarchical clustering, in WWW '06: Proceedings of the 15th international conference on World Wide Web. 2006, ACM Press: New York, NY, USA. p. 625-632.

当用户标记内容或信息时，比如网页、照片、视频、播客、 tweets、科学论文等，就会形成一种协同标记模式。Strohmaier et al阐述了这个概念：“标签”一词是指”用户自愿用所谓的‘标签’注释资源的活动——从无限制和不受控制的词汇中自由选择”。其他人将标签解释为一个非结构化的文本 。

Folksonomies consist of three basic entities: users, tags, and resources. Users create tags to mark resources such as: web pages, photos, videos, and podcasts. These tags are used to manage, categorize and summarize online content. This collaborative tagging system also uses these tags as a way to index information, facilitate searches and navigate resources. Folksonomy also includes a set of URLs that are used to identify resources that have been referred to by users of different websites. These systems also include category schemes that have the ability to organize tags at different levels of granularity.[22]

Folksonomies consist of three basic entities: users, tags, and resources. Users create tags to mark resources such as: web pages, photos, videos, and podcasts. These tags are used to manage, categorize and summarize online content. This collaborative tagging system also uses these tags as a way to index information, facilitate searches and navigate resources. Folksonomy also includes a set of URLs that are used to identify resources that have been referred to by users of different websites. These systems also include category schemes that have the ability to organize tags at different levels of granularity.Berlin, B. (1992). Ethnobiological Classification. Princeton: Princeton University Press.

协同标记由三个基本实体组成: 用户、标签和资源。用户创建标签来标记网页、照片、视频、播客等资源。这些标签用于管理、分类和总结在线内容。这个分众分类法系统也使用这些标签作为索引信息，方便搜索和浏览资源的方式。协同标记还包括一组 url，用于识别不同网站用户引用的资源。这些系统还包括能够按不同粒度级别组织标签的分类方案。

Vander Wal identifies two types of folksonomy: broad and narrow.[23] A broad folksonomy arises when multiple users can apply the same tag to an item, providing information about which tags are the most popular. A narrow folksonomy occurs when users, typically fewer in number and often including the item's creator, tag an item with tags that can each be applied only once. While both broad and narrow folksonomies enable the searchability of content by adding an associated word or phrase to an object, a broad folksonomy allows for sorting based on the popularity of each tag, as well as the tracking of emerging trends in tag usage and developing vocabularies.[23]

Vander Wal identifies two types of folksonomy: broad and narrow. A broad folksonomy arises when multiple users can apply the same tag to an item, providing information about which tags are the most popular. A narrow folksonomy occurs when users, typically fewer in number and often including the item's creator, tag an item with tags that can each be applied only once. While both broad and narrow folksonomies enable the searchability of content by adding an associated word or phrase to an object, a broad folksonomy allows for sorting based on the popularity of each tag, as well as the tracking of emerging trends in tag usage and developing vocabularies.

范德 · 沃尔确定了两种类型的协同标记方法: 广义协同标记和狭义协同标记。当多个用户可以对一个项目应用相同的标记，并提供关于哪些标记最受欢迎的信息时，就会形成广义的协同标记。而狭义的协同标记法发生在用户使用标签标记一个项目的时候，这些标签通常数量较少，并且通常包括项目的创建者，每个项目只能应用一次。虽然广义协同标记法和狭义协同标记都通过向对象添加关联词或短语来实现内容的可搜索性，但广义协同标记允许根据每个标签的流行程度进行排序，并跟踪标签使用和发展词汇表的新趋势。

An example of a broad folksonomy is del.icio.us, a website where users can tag any online resource they find relevant with their own personal tags. The photo-sharing website Flickr is an oft-cited example of a narrow folksonomy.

An example of a broad folksonomy is del.icio.us, a website where users can tag any online resource they find relevant with their own personal tags. The photo-sharing website Flickr is an oft-cited example of a narrow folksonomy.

作为广义协同标记的网站， del.icio.us允许用户使用自己的个人标签标记任何他们发现的相关的在线资源的网站。 Flickr 作为一个照片分享网站，是狭义协同标记的典型例子。

协同标记与分类方法

'Taxonomy' refers to a hierarchical categorization in which relatively well-defined classes are nested under broader categories. A folksonomy establishes categories (each tag is a category) without stipulating or necessarily deriving a hierarchical structure of parent-child relations among different tags. (Work has been done on techniques for deriving at least loose hierarchies from clusters of tags.[24])

'Taxonomy' refers to a hierarchical categorization in which relatively well-defined classes are nested under broader categories. A folksonomy establishes categories (each tag is a category) without stipulating or necessarily deriving a hierarchical structure of parent-child relations among different tags. (Work has been done on techniques for deriving at least loose hierarchies from clusters of tags.)

“分类法”是指一种层次分类，将定义相对良好的类被嵌套在更广泛的类别中。协同标记建立的分类目录，不规定或者必须在不同的标签之间的道父子关系的层次结构类别，即每个标记就是一个类别(已经有从标签集群中至少衍生出松散层次结构的技术)。

Supporters of folksonomies claim that they are often preferable to taxonomies because folksonomies democratize the way information is organized, they are more useful to users because they reflect current ways of thinking about domains, and they express more information about domains.[25] Critics claim that folksonomies are messy and thus harder to use, and can reflect transient trends that may misrepresent what is known about a field.

Supporters of folksonomies claim that they are often preferable to taxonomies because folksonomies democratize the way information is organized, they are more useful to users because they reflect current ways of thinking about domains, and they express more information about domains. Critics claim that folksonomies are messy and thus harder to use, and can reflect transient trends that may misrepresent what is known about a field.

支持 协同标记的人声称，他们通常比分类法更可取，因为协同标记使信息的组织方式民主化，他们对用户更有用，因为他们反映了当前对领域的思考方式，他们表达了更多关于领域的信息。批评者声称，协同标记杂乱无章，难以使用，而且反映出的短暂趋势可能会歪曲某一领域的已知信息。

An empirical analysis of the complex dynamics of tagging systems, published in 2007,[26] has shown that consensus around stable distributions and shared vocabularies does emerge, even in the absence of a central controlled vocabulary. For content to be searchable, it should be categorized and grouped. While this was believed to require commonly agreed on sets of content describing tags (much like keywords of a journal article), some research has found that in large folksonomies common structures also emerge on the level of categorizations.[27] Accordingly, it is possible to devise mathematical models of collaborative tagging that allow for translating from personal tag vocabularies (personomies) to the vocabulary shared by most users.[28]

An empirical analysis of the complex dynamics of tagging systems, published in 2007,Harry Halpin, Valentin Robu, Hana Shepherd The Complex Dynamics of Collaborative Tagging, Proc. International Conference on World Wide Web, ACM Press, 2007. has shown that consensus around stable distributions and shared vocabularies does emerge, even in the absence of a central controlled vocabulary. For content to be searchable, it should be categorized and grouped. While this was believed to require commonly agreed on sets of content describing tags (much like keywords of a journal article), some research has found that in large folksonomies common structures also emerge on the level of categorizations.V. Robu, H. Halpin, H. Shepherd Emergence of consensus and shared vocabularies in collaborative tagging systems, ACM Transactions on the Web (TWEB), Vol. 3(4), art. 14, 2009. Accordingly, it is possible to devise mathematical models of collaborative tagging that allow for translating from personal tag vocabularies (personomies) to the vocabulary shared by most users.Robert Wetzker, Carsten Zimmermann, Christian Bauckhage, and Sahin Albayrak I tag, you tag: translating tags for advanced user models, Proc. International Conference on Web Search and Data Mining, ACM Press, 2010.

2007年发表的一篇关于复动力学标签系统的实证分析表明，即使在没有核心受控词表的情况下，围绕稳定发布和共享词汇表的共识也确实出现了。对于可搜索的内容，应该对其进行分类和分组。虽然大家普遍认为需要像期刊关键词一样，在描述标签的内容集上达成共识。但是一些研究发现，在一些常见的目录水平的协同标记结构也出现了。因此，我们可以设计出协同设计的数学模型，从而将个人标记词汇转换为更加大众化的词汇。

Folksonomy is unrelated to folk taxonomy, a cultural practice that has been widely documented in anthropological and folkloristic work. Folk taxonomies are culturally supplied, intergenerationally transmitted, and relatively stable classification systems that people in a given culture use to make sense of the entire world around them (not just the Internet).[22]

Folksonomy is unrelated to folk taxonomy, a cultural practice that has been widely documented in anthropological and folkloristic work. Folk taxonomies are culturally supplied, intergenerationally transmitted, and relatively stable classification systems that people in a given culture use to make sense of the entire world around them (not just the Internet).

协同标记与民间分类法无关，这种文化实践在人类学和民间分类学著作中得到了广泛的记载。民间分类法是文化上提供的、代际间传播的、相对稳定的分类系统，特定文化中的人们使用这些系统来理解他们周围的整个世界，而不仅仅是互联网。

The study of the structuring or classification of folksonomy is termed folksontology.[29] This branch of ontology deals with the intersection between highly structured taxonomies or hierarchies and loosely structured folksonomy, asking what best features can be taken by both for a system of classification. The strength of flat-tagging schemes is their ability to relate one item to others like it. Folksonomy allows large disparate groups of users to collaboratively label massive, dynamic information systems. The strength of taxonomies are their browsability: users can easily start from more generalized knowledge and target their queries towards more specific and detailed knowledge.[30] Folksonomy looks to categorize tags and thus create browsable spaces of information that are easy to maintain and expand.

The study of the structuring or classification of folksonomy is termed folksontology. This branch of ontology deals with the intersection between highly structured taxonomies or hierarchies and loosely structured folksonomy, asking what best features can be taken by both for a system of classification. The strength of flat-tagging schemes is their ability to relate one item to others like it. Folksonomy allows large disparate groups of users to collaboratively label massive, dynamic information systems. The strength of taxonomies are their browsability: users can easily start from more generalized knowledge and target their queries towards more specific and detailed knowledge.Trattner, C., Körner, C., Helic, D.: Enhancing the Navigability of Social Tagging Systems with Tag Taxonomies. In Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies, ACM, New York, NY, USA, 2011 Folksonomy looks to categorize tags and thus create browsable spaces of information that are easy to maintain and expand.

研究协同标记的结构或分类称为协同分类学。本体论的这个分支处理高度结构化的分类或层次结构与协同标记之间的交叉，寻找对于一个分类系统来说可以采用的最佳特性有哪些。平面标签方案的优势在于它们能够将一个项目与类似的其他项目联系起来。协同标记则允许大型不同用户群体协作标记大规模的动态信息系统。分类法的优势在于它们的可浏览性: 用户可以很容易地从更广泛的知识开始，并将他们的查询定向到更具体和详细的知识。 如果系统标记能够对标签进行分类，则可以创建易于维护和扩展的可浏览的信息空间。

用于知识获取的社会化标签

Social tagging for knowledge acquisition is the specific use of tagging for finding and re-finding specific content for an individual or group. Social tagging systems differ from traditional taxonomies in that they are community-based systems lacking the traditional hierarchy of taxonomies. Rather than a top-down approach, social tagging relies on users to create the folksonomy from the bottom up.[31]

Social tagging for knowledge acquisition is the specific use of tagging for finding and re-finding specific content for an individual or group. Social tagging systems differ from traditional taxonomies in that they are community-based systems lacking the traditional hierarchy of taxonomies. Rather than a top-down approach, social tagging relies on users to create the folksonomy from the bottom up.Held, C., & Cress, U. (2009). Learning by Foraging: The impact of social tags on knowledge acquisition. In Learning in the synergy of multiple disciplines (pp. 254-266). Springer Berlin Heidelberg.

知识获取的社会标签是为个人或群体寻找和重新寻找特定内容而使用的特定标签。社会标签系统不同于传统的分类系统，因为它们是基于社区的系统，缺乏传统的分类系统等级。社会标签不是自顶向下的方法，而是依靠用户自下而上地创建大众分类法。赫尔德，c. ，& 克莱斯，美国。(2009).在觅食中学习: 社会标签对知识获取的影响。在多学科协同学习中(pp。254-266).Springer Berlin Heidelberg.

Common uses of social tagging for knowledge acquisition include personal development for individual use and collaborative projects. Social tagging is used for knowledge acquisition in secondary, post-secondary, and graduate education as well as personal and business research. The benefits of finding/re-finding source information are applicable to a wide spectrum of users. Tagged resources are located through search queries rather than searching through a more traditional file folder system.[32] The social aspect of tagging also allows users to take advantage of metadata from thousands of other users.[31]

Common uses of social tagging for knowledge acquisition include personal development for individual use and collaborative projects. Social tagging is used for knowledge acquisition in secondary, post-secondary, and graduate education as well as personal and business research. The benefits of finding/re-finding source information are applicable to a wide spectrum of users. Tagged resources are located through search queries rather than searching through a more traditional file folder system.Fu, W. (2008). The microstructures of social tagging: a rational model. In: Proceedings of the ACM 2008 Conference on Computer Supported Cooperative Work, pp. 229–238. ACM, New York. The social aspect of tagging also allows users to take advantage of metadata from thousands of other users.

社会标签在获取知识方面的常见用途包括个人发展和协作项目。社会标签用于中学、高等教育、研究生教育以及个人和商业研究中的知识获取。查找/重新查找源信息的好处适用于范围广泛的用户。标记的资源是通过搜索查询定位的，而不是通过更传统的文件夹 system.Fu，w (2008)进行搜索。社会标签的微观结构: 一个理性模型。参见: ACM 2008计算机支持的协同工作会议论文集，第页。229–238.美国计算机协会，纽约。标签的社会化方面也允许用户利用来自成千上万其他用户的元数据。

Users choose individual tags for stored resources. These tags reflect personal associations, categories, and concepts. All of which are individual representations based on meaning and relevance to that individual. The tags, or keywords, are designated by users. Consequently, tags represent a user's associations corresponding to the resource. Commonly tagged resources include videos, photos, articles, websites, and email.[33] Tags are beneficial for a couple of reasons. First, they help to structure and organize large amounts of digital resources in a manner that makes them easily accessible when users attempt to locate the resource at a later time. The second aspect is social in nature, that is to say that users may search for new resources and content based on the tags of other users. Even the act of browsing through common tags may lead to further resources for knowledge acquisition.[31]

Users choose individual tags for stored resources. These tags reflect personal associations, categories, and concepts. All of which are individual representations based on meaning and relevance to that individual. The tags, or keywords, are designated by users. Consequently, tags represent a user's associations corresponding to the resource. Commonly tagged resources include videos, photos, articles, websites, and email.Kimmerle, J., Cress, U., & Held, C. (2010). The interplay between individual and collective knowledge: technologies for organisational learning and knowledge building. Knowledge Management Research & Practice, 8(1), 33-44. Tags are beneficial for a couple of reasons. First, they help to structure and organize large amounts of digital resources in a manner that makes them easily accessible when users attempt to locate the resource at a later time. The second aspect is social in nature, that is to say that users may search for new resources and content based on the tags of other users. Even the act of browsing through common tags may lead to further resources for knowledge acquisition.

用户为存储的资源选择单独的标记。这些标签反映了个人联系、类别和概念。所有这些都是基于个人意义和相关性的个人表述。这些标签或者关键字是由用户指定的。因此，标记表示与资源对应的用户关联。通常标记的资源包括视频、照片、文章、网站和电子邮件。个人和集体知识之间的相互作用: 组织学习和知识建设的技术。知识管理研究与实践，8(1) ，33-44。标签是有益的，有几个原因。首先，它们帮助构建和组织大量的数字资源，以便当用户以后试图查找资源时能够方便地访问这些资源。第二个方面是社会化的本质，也就是说用户可以根据其他用户的标签来搜索新的资源和内容。甚至通过普通标签浏览也可能为获取知识提供更多的资源。

Tags that occur more frequently with specific resources are said to be more strongly connected. Furthermore, tags may be connected to each other. This may be seen in the frequency in which they co-occur. The more often they co-occur, the stronger the connection. Tag clouds are often utilized to visualize connectivity between resources and tags. Font size increases as the strength of association increases.[33]

Tags that occur more frequently with specific resources are said to be more strongly connected. Furthermore, tags may be connected to each other. This may be seen in the frequency in which they co-occur. The more often they co-occur, the stronger the connection. Tag clouds are often utilized to visualize connectivity between resources and tags. Font size increases as the strength of association increases.

使用特定资源出现得更频繁的标记被认为是连接性更强的标记。此外，标记可以相互连接。这可以从它们共同出现的频率中看出来。它们共同出现的次数越多，联系就越紧密。标记云通常用于可视化资源和标记之间的连接。字体大小随着关联强度的增加而增加。

Tags show interconnections of concepts that were formerly unknown to a user. Therefore, a user's current cognitive constructs may be modified or augmented by the metadata information found in aggregated social tags. This process promotes knowledge acquisition through cognitive irritation and equilibration. This theoretical framework is known as the co-evolution model of individual and collective knowledge.[33]

Tags show interconnections of concepts that were formerly unknown to a user. Therefore, a user's current cognitive constructs may be modified or augmented by the metadata information found in aggregated social tags. This process promotes knowledge acquisition through cognitive irritation and equilibration. This theoretical framework is known as the co-evolution model of individual and collective knowledge.

标签显示了以前用户不知道的概念之间的相互联系。因此，用户当前的认知结构可能会被聚合的社会标签中的元数据信息修改或增强。这个过程通过认知刺激和平衡促进知识的获得。这个理论框架被称为个体和集体知识的协同进化模型。

The co-evolution model focuses on cognitive conflict in which a learner's prior knowledge and the information received from the environment are dissimilar to some degree.[31][33] When this incongruence occurs, the learner must work through a process cognitive equilibration in order to make personal cognitive constructs and outside information congruent. According to the coevolution model, this may require the learner to modify existing constructs or simply add to them.[31] The additional cognitive effort promotes information processing which in turn allows individual learning to occur.[33]

The co-evolution model focuses on cognitive conflict in which a learner's prior knowledge and the information received from the environment are dissimilar to some degree. When this incongruence occurs, the learner must work through a process cognitive equilibration in order to make personal cognitive constructs and outside information congruent. According to the coevolution model, this may require the learner to modify existing constructs or simply add to them. The additional cognitive effort promotes information processing which in turn allows individual learning to occur.

协同进化模型着眼于认知冲突，即学习者的先验知识和从环境中获得的信息在一定程度上是不同的。当这种不一致发生时，学习者必须通过一个认知平衡的过程来使个人认知结构和外部信息一致。根据共同进化模型，这可能需要学习者修改现有的构造或者简单地添加到它们中。额外的认知努力促进了信息处理，而信息处理又促进了个体学习的发生。

Examples

  • BibSonomy: social bookmarking and publication-sharing system
  • del.icio.us: public tagging service
  • Diigo: social bookmarking website
  • Flickr: shared photos
  • Instagram: online photo-sharing and social networking service
  • Many libraries' online catalogsSteele, T. (2009). The new cooperative cataloging. Library Hi Tech, 27 (1), 68-77Corey A. Harper and Barbara B. Tillett, Library of Congress controlled vocabularies and their application to the Semantic Web
  • Mendeley: social reference management software
  • Pinterest: photosharing and publishing website
  • Steam video game store
  • StumbleUpon: content discovery engine
  • Twitter hashtags
  • The World Wide Web Consortium's Annotea project with user-generated tags in 2002.
  • WordPress: blogging tool and Content Management System
  • Tumblr tags


  • BibSonomy: 社会性书签和出版物分享系统
  • del.icio.us: public tagging service
  • Diigo: 社会性书签网站
  • Flickr: shared photos
  • Instagram: online photo-sharing and social networking
  • 许多图书馆的在线目录/目录 t。新型合作编目。图书馆高科技，27(1) ，68-77 corey a. Harper 和 Barbara b. Tillett，国会图书馆控制的词汇及其在语义网上的应用
  • Mendeley: 社会参考管理软件
  • Pinterest: 照片分享和出版网站
  • Steam 视频游戏商店
  • StumbleUpon: 内容发现引擎
  • Twitter 标签
  • 2002年美国万维网联盟的 Annotea 项目，用户生成标签。博客工具和内容管理系统

See also


  • Autotagging
  • Blogosphere
  • Collective intelligence
  • Enterprise bookmarking
  • Faceted classification
  • Hierarchical clustering
  • Semantic annotation
  • Semantic similarity
  • Thesaurus
  • Weak ontology
  • Wiki


  • autotaging
  • Blogosphere
  • Collective intelligence
  • Enterprise bookmarking
  • 刻面分类
  • hierarchian clustering
  • Semantic annotation
  • Semantic similarity
  • 叙词表
  • Weak ontology
  • Wiki

References

{{Reflist|30em|refs = Bateman, S., Brooks, C., McCalla, G., & Brusilovsky, P. (2007, May). Applying collaborative tagging to e-learning. In Proceedings of the 16th International World Wide Web Conference (WWW2007).

  1. ↑ Peters, Isabella (2009). "Folksonomies. Indexing and Retrieval in Web 2.0". Berlin: De Gruyter Saur. ISBN 9783598251795. (isabella-peters.de)
  2. ↑ Pink, Daniel H. (11 December 2005). "Folksonomy". New York Times. Retrieved 14 July 2009.
  3. ↑ Lambiotte, R; Ausloos, M. (2005). Computational Science – ICCS 2006. Lecture Notes in Computer Science. 3993. pp. 1114–1117. arXiv:cs.DS/0512090. doi:10.1007/11758532_152. ISBN 978-3-540-34383-7. 
  4. ↑ Borne, Kirk. "Collaborative Annotation for Scientific Data Discovery and Reuse". Bulletin of Association for Information Science and Technology. ASIS&T. Archived from the original on 5 March 2016. Retrieved 26 May 2016.
  5. ↑ 5.0 5.1 Vander Wal, Thomas (11 December 2005). "Folksonomy Coinage and Definition".
  6. ↑ Vander Wal, T. (2005). "Off the Top: Folksonomy Entries." Visited November 5, 2005. See also: Smith, Gene. "Atomiq: Folksonomy: social classification." Aug 3, 2004. Retrieved January 1, 2007.
  7. ↑ Origin of the term
  8. ↑ Lamere, Paul (June 2008). "Social Tagging And Music Information Retrieval". Journal of New Music Research. 37 (2): 101–114. CiteSeerX 10.1.1.492.2457. doi:10.1080/09298210802479284. S2CID 17063867.
  9. ↑ Bryzgalin, E.A.; Voiskounsky, A.E.; Kozlovskiy, S.A. (1 September 2019). "Psychological Analysis of Practical Experience in "Wikipedia" Development". Sibirskiy Psikhologicheskiy Zhurnal (73): 17–39. doi:10.17223/17267080/73/2.
  10. ↑ Gupta, M., et al., An Overview of Social Tagging and Applications, in Social Network Data Analytics, C.C. Aggarwal, Editor. 2011, Springer. p. 447-497.
  11. ↑ Quintarelli, E., Folksonomies: power to the people. 2005.
  12. ↑ Mathes, A., Folksonomies - Cooperative Classification and Communication Through Shared Metadata. 2004.
  13. ↑ Wal, T.V. Folksonomy. 2007
  14. ↑ Kipp, M. and D.G. Campbell, Patterns and Inconsistencies in Collaborative Tagging Systems: An Examination of Tagging Practices. Proceedings Annual General Meeting of the American Society for Information Science and Technology, 2006.
  15. ↑ Hayman, S., Folksonomies and Tagging: New developments in social bookmarking, in Proceedings of Ark Group Conference: Developing and Improving Classification Schemes, 2007, Sydney. 2007: Sydney.
  16. ↑ Kroski, E., The Hive Mind: Folksonomies and User-Based Tagging. 2005
  17. ↑ Guy, M. and E. Tonkin, Folksonomies: Tidying up Tags? D-Lib Magazine, 2006. 12(Number 1): p. 1-15.
  18. ↑ Strohmaier, M., C. Körner, and R. Kern, Understanding why users tag: A survey of tagging motivation literature and results from an empirical study. Web Semantics: Science, Services and Agents on the World Wide Web, 2012. 17: p. 1-11.
  19. ↑ Ames, M.N.M., Why We Tag: Motivations for Annotation in Mobile and Online Media, in SIGCHI conference on Human factors in computing systems. 2007, ACM Press: New York, NY, USA. p. 971-980.
  20. ↑ Guy, M. and E. Tonkin, Folksonomies: Tidying up Tags? D-Lib Magazine, 2006. 12(Number 1): p. 1-15.
  21. ↑ Brooks, C.H. and N. Montanez, Improved annotation of the blogosphere via autotagging and hierarchical clustering, in WWW '06: Proceedings of the 15th international conference on World Wide Web. 2006, ACM Press: New York, NY, USA. p. 625-632.
  22. ↑ 22.0 22.1 Berlin, B. (1992). Ethnobiological Classification. Princeton: Princeton University Press.
  23. ↑ 23.0 23.1 Vander Wal, Thomas. "Explaining and Showing Broad and Narrow Folksonomies". Retrieved 2013-03-05.
  24. ↑ Laniado, David. "Using WordNet to turn a folksonomy into a hierarchy of concepts" (PDF). CEUR Workshop Proceedings. 314 (51). Retrieved 7 August 2015.
  25. ↑ Weinberger, David. "Folksonomy as Symbol". Joho the Blog. Retrieved 7 August 2015.
  26. ↑ Harry Halpin, Valentin Robu, Hana Shepherd The Complex Dynamics of Collaborative Tagging, Proc. International Conference on World Wide Web, ACM Press, 2007.
  27. ↑ V. Robu, H. Halpin, H. Shepherd Emergence of consensus and shared vocabularies in collaborative tagging systems, ACM Transactions on the Web (TWEB), Vol. 3(4), art. 14, 2009.
  28. ↑ Robert Wetzker, Carsten Zimmermann, Christian Bauckhage, and Sahin Albayrak I tag, you tag: translating tags for advanced user models, Proc. International Conference on Web Search and Data Mining, ACM Press, 2010.
  29. ↑ Van Damme, Céline; et al. "FolksOntology: An Integrated Approach for Turning Folksonomies into Ontologies" (PDF). Retrieved April 20, 2012.
  30. ↑ Trattner, C., Körner, C., Helic, D.: Enhancing the Navigability of Social Tagging Systems with Tag Taxonomies. In Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies, ACM, New York, NY, USA, 2011
  31. ↑ 31.0 31.1 31.2 31.3 31.4 Held, C., & Cress, U. (2009). Learning by Foraging: The impact of social tags on knowledge acquisition. In Learning in the synergy of multiple disciplines (pp. 254-266). Springer Berlin Heidelberg.
  32. ↑ Fu, W. (2008). The microstructures of social tagging: a rational model. In: Proceedings of the ACM 2008 Conference on Computer Supported Cooperative Work, pp. 229–238. ACM, New York.
  33. ↑ 33.0 33.1 33.2 33.3 33.4 Kimmerle, J., Cress, U., & Held, C. (2010). The interplay between individual and collective knowledge: technologies for organisational learning and knowledge building. Knowledge Management Research & Practice, 8(1), 33-44.
  34. ↑ Steele, T. (2009). The new cooperative cataloging. Library Hi Tech, 27 (1), 68-77
  35. ↑ Corey A. Harper and Barbara B. Tillett, Library of Congress controlled vocabularies and their application to the Semantic Web

温伯格(2007)。一切都是杂乱无章的: 新数字混乱的力量。纽约时报书店

External links

  • "Folksonomy", The New York Times, 2005-12-11
  • "Folksonomies Tap People Power", Wired News, 2005-02-01
  • Folksonomies as a tool for professional scientific databases
  • "The Three Orders": 2005 explanation of tagging and folksonomies (Archived version)
  • Vanderwal's definition of folksonomy
  • Vanderwal's take on Wikipedia's definition of folksonomy
  • Classroom Collaboration Using Social Bookmarking Service Diigo


  • “ Folksonomy”，纽约时报，2005-12-11
  • “ Folksonomies Tap People Power”，Wired News，2005-02-01
  • Folksonomies as a tool for professional scientific databases
  • “ The Three Orders”: 2005 explaining of tagging and Folksonomy (Archived version)
  • Vanderwal 对 Folksonomy 的定义
  • 采用了维基百科对大众分类的定义
  • 使用社会性书签服务 Diigo 进行协作

模板:Web syndication 模板:Semantic Web


Category:Collective intelligence Category:Knowledge representation Category:Metadata Category:Semantic Web Category:Social bookmarking Category:Taxonomy Category:Web 2.0 neologisms Category:Sociology of knowledge Category:Information architecture

类别: 集体智慧类别: 知识表示类别: 元数据类别: 语义网类别: 社会性书签类别: 分类类别: Web 2.0新词类别: 知识社会学类别: 信息架构


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