Why We Tag and How We Tag:

1. Why We Tag and How We Tag: Understanding User Tagging Behavior on a Chinese Social Sharing Site Li He

2. What is Tagging? • Collaborative social tagging: assign free-form descriptive terms, also known as tags, to resources • Social aspect of tagging: publicly tag one’s own content and browse the annotated and categorized content of other people • Personal aspect of tagging: manage one’s resources by his/her own vocabulary and categorization methods

3. What is Tagging? • Collaborative tagging offers – • An alternative to having an authority, such as a librarian, to perform categorizing and indexing, making users the ones who impact how the whole community perceives the content • A new way to personalize the process of information organization and information exchange. Users have much more freedom to handle and make sense of their own information as well as that of the others.

4. Tagging in China： • Chinese websites have been following the collaborative tagging trend. Although the adoption rate of tagging by Chinese Internet users was reported to be as low as 2.3% by the beginning of 2007, more and more Chinese Blog Service Provider, social bookmarking sites and social sharing sites similar to Flikr and Youtube have incorporated tagging, and it now becomes almost a standard feature on social sites. It could be expected that tagging will be a more common practice for Chinese Internet users.

5. Purpose of Study： • This study analyzes a Chinese social site Douban.com, the most influential Chinese book, music and movie recommendation community. The research focus on the tagging activity on Douban, and will try to find out: • Usage patterns and behaviors of annotation and tagging on Douban • Douban users' motivations for tagging content in this system • Comparison of Chinese taggers and Western taggers on the above-discussed aspects

6. Related Work 1：Golder & Huberman • Analyzed the structure of Deli.cio.us and examined how it evolves over time with two data sets, URLs and a random sample of 229 users, derived in a 5-day timeframe. • Major findings: • The number of bookmarks a user has created and the number of tags they used have a weak relationship • Users' tag lists gradually grow as they discover new interests and add new tags to categorize and describe them • There is a stability in the relative proportions of tags within a given URL • Tags can be categorized into 7 possible kinds

7. Related Work 2：Marlow et al. • Described a model of tagging systems that consists of three individual elements: resources, users and tags • Provided a 7-dimesion taxonomy of tagging systems for design • Categorized user tagging incentives into two high-level practices and six potential motivations • Findings from studying Flikr with the above frameworks: • The number of bookmarks a user has created and the number of tags they used have a weak relationship • The interaction between user, tag, and usage varied a lot

8. Other Related Works： • Ames & Naaman: interviewedFlikr users; offered another taxonomy of motivations for tagging along the two dimensions of sociality and function; suggest that social incentives for tagging appear to be particularly important in motivating users to tag • Kipp: compared tagging on Del.icio.us and CiteULike to traditional cataloging; suggests that users employ a wide variety of conventions in constructing tags, which extends beyond the traditional objectives of subject access, and expresses a dynamic relationship between document and user, and between subject and task • Zollers: studied Amazon.com and Last.fm; concludes 3 emergent social motivations, include expression, performance, and activism for tagging.

9. Douban.com: • “Douban” literally means one individual pea in a peapod, but it actually is the name of a Hutong (narrow alley, a traditional architecture unique to Beijing) where the site founder lives. • The main purpose of Douban, as it is stated on the site, is to: "… help you to find the people who shares your interests in movie, music, and books, and discover more good stuff through them." [1]

10. Douban.com: • A resource page on Douban

11. Douban.com • A user’s (me)main page on Douban

12. Douban.com: • A user’s (me) book page on Douban

13. Tagging on Douban.com • Douban has the following dimensions according to the taxonomy of tagging system suggested by Marlow et al:

14. Tagging on Douban.com • Suggestive tagging interface:

15. Tagging on Douban.com • Douban manifests the social and personal characteristics of collaborative tagging system found on similar English sites such as Del.icio.us and Flikr. The design decisions of the system imply that tags and tagging have three meanings on Douban: • They can be used for Personal Information Management as users interact with their tag pools to categorize and retrieve their own collections. • They help support interest discovery and sharing by linking users to one another through tags assigned to resources. • They provide additional access points for searching and navigation since the system’s default search for a resource is not full-text based, and will only match the search terms with the bibliographic information harvested and indexed by the system.

16. Methodology：1. Data Collection Three sets of Douban data were derived in a 30-day timeframe, from October 13th to November 12th. • Data Set 1: 7 Douban Users. For each user, the following data were collected on a daily base: • Total number of tags inthe tag pools; • Total number of distinct tag (tag that has been used only once); • Total number of saved resources; On the last day of the data collection period, the 7 users' tags were all derived for a content analysis

17. Methodology：1. Data Collection • Data Set 2: Tags • The top 5 most highly used tags of each resource type were collected and their numbers of total usage were recorded on a daily base. The total number of tags of all three tag types, defined as the total number of tags[1] in the system, and the total number of Douban users were also recorded at the same frequency. • A one-time data collection of the numbers of tags that fall into different usage ranges (e.g. used 1 time, used 1,000 – 4,999 times) were conducted for movie, book and music tags.

18. Methodology：1. Data Collection • Data Set 3: Resources. 1. The following data were collected on a daily base for 5 books, 5 music albums and 5 movies : • Total number of tags assigned the resource • Total number of times a tag is assigned to the resource, for each of the most popular 8 tags that are displayed on the resource's page • Total number of users that have saved this resource 2. The resource(s) saved by the 7 users during the data collection period and the most popular 8 tags assigned to them

19. Methodology：2. Content Analysis • Coding schema

20. Methodology：3. Interview • The invitation email for aninterview was first sent to the 7 users that have been observed for one-month. Only 3 were willing to accept the invitation. The invitation was then sent to another group of users who met the original selection criteria. In the end, a total of 8 users (all mainland Chinese) were interviewed independently using Instant Messengers. The interview sessions lasted from 20-30 minutes. • The questions in the interview are all open-ended ones. Interviewees were asked about their tagging habit, and opinions about tags, tagging and tagging system. The conversations were transcribed and then translated into English for further analysis.

21. Results & Discussions：1. General Tag Usage

22. Results & Discussions：1. General Tag Usage V=movie tag; B=book tag; M=music tag

23. Results & Discussions：2. Tag Usage for Resources • The graph shows the growth of the total number of tags of 9 resources. Each point on the graph shows the total number of tags (Y-axis) at a daily increase of people who have saved the resource (X-axis). In general, the quantitycontinues to increase at a steady rate.

24. Results & Discussions：2. Tag Usage for Resources The left graph shows the proportion changes of each of the 8 most popular tagsfor one resource. Obviously, each tag’s use frequency is a nearly fixed proportion. The most popular one tends to grow a little bit more, but the less used ones remain quite stable. This conclusion is again confirmed when we look at the proportion changes of the most popular tag of the 15 resources. The lines are all fairly flat.

25. Results & Discussions：2. Tag Usage for Resources • The graph shows the coding results of the 8 most popular tags for each of the 210 resources, which were saved by the 7 users during the data collection period. 37 are books, 52 are music albums and 121 are movies. Some obvious patterns include: • The most popular tags for a resource generallyinclude the title of the resource, its creator/contributor, and where it is produced, which is quite similar to the index terms a professional indexer would use. • Name tags and Category tags are usually the most frequently used tags; Subject tags are much more highly used for movies and books.

26. Results & Discussions：2. Tag Usage for Resources The graph shows the proportion of each kind of tags for movie resources of different popularity. Opinion tags and Self Reference tags gradually go off the main stage as more people save the resource. While the proportions of Name tags and Category tags remain almost the same; Title tags, on the other hand, exhibit an apparent increase.

27. Results & Discussions：3.1 User Activities In general, the tag pool size of the 7 observed users is growing over time as they add more resources. But their resource and tag collection sizes and the relationship between the twoshow quite a degree of variance. Some users have a large resource collection but a small tag pool, while some build their tag pools faster than saving resources.

28. Results & Discussions：3.1 User Activities The graph is the coding result of the total tags of the 7 users. The left part shows the percentage of each kind of tag by weight (times of use), the right part shows the percentage by the quantity of that kind of tag. The constitution of a user’s tag pool is quite similar to that of the most popular tags for a resource. Again, Name tags take up the largest part, and are frequently used. The two Keyword tags, Category and Subject tags are also very often assigned to resources, followed by Region tags. Opinion tags and Self Reference tags are comparatively much less used. Two users don’t have any Personal tag at all.

29. Result & Discussion：3.1 User Activities Percentages of Keyword tags in the tag pool generally increase when calculated by weight, while that of the Name tag decrease. This is extremely obvious for User3. Besides name variations discussed above, it is possible that Name tags serve more as additional access points for others and, while Descriptor tags, especially Category tags are used for retrieval.

30. Results & Discussions：3.2 User Opinions • Tagging Motivations: 1. Personal Information Management All respondents stated that their primary purpose of tagging is to better manage their collection for future retrieval. 2. Interest Discovery Only 1 respondent mentioned this motivation; others agreed it could be one of the motivationsin the follow-up question, but they didn’t consciously tag for this purpose. Surprisingly, other motivations suggested by the literature in the English world, such as Attract Attention, Self Presentation, Performance, Communication were not recognized by the respondent.

31. Results & Discussions：3.2 User Opinions • Tagging Habits: 1. Random or systematic? Only 1 respondent replied that he always tags randomly. Others stated that they have a clear idea of what to tag and how to make use of tags. A summary of their replies suggests: • They become much more systematic after tagging for a period of time, and would follow certain rules when they tag, such as using a consistent format for non-Chinese names, control the number of Category tags, assigning the same group of tags (Name, Region, Category, etc) according to the resource type (Movie, Book or Music). • They would be as exact as possible when they tag a resource, whereas comprehensiveness is less often pursued because they are more concerned about tagging the facet of the resource that interest them. • They show a willingness to contribute tags to resources they have interests in, so as to create access points for others.

32. Results & Discussions：3.2 User Opinions • Tagging Habits: 2. Tag preference • The respondents generally consider good tags as those helpful for faster retrieval and finding their special interests, such as a non-mainstream music/movie genres or less popular persons. Name tags and Category tags are highly preferred. • While most respondents expressed much less interest in Personal tags, 2 people stated that some tags are too general to help with retrieval and they intended to use more personalized tags in the future, such as specifying categorizations.

33. Results & Discussions：3.2 User Opinions • Tagging Habits: 3. Interactions with the tagging system • All respondents said they will use the tags suggested by the system if they find the tags appropriate. • Respondents seldom or never specifically search for a tag. • The preference of tag cloud or tag list for tag display varied by person. Those who like tag cloud said it looks fun and gives a direct impression of the person’s interests; while those that prefer tag list think it is more clear and in a better order.

34. Results & Discussions：3.2 User Opinions • Tagging Habits: 4. Tag management Several respondents said that they were clueless when they first knew about tagging, having no idea of what tagging can do for them. And they just followed others. As they gained more experience, more systematic tagging habits were developed. They would then notice there is a certain amount of repetitive (functionally or semantically) tags and tags that they have little use of.But they find it “difficult”, “tiring” and “very time-consuming” to edit them, and would do so only when they are really idle. Main tag management activities include: • Fix factual errors. Such as to correct spelling mistakes and inconsistent name formats. • Combine or break down Category tags. • Refine Subject tags. Such as to reduce synonyms.

35. Results & Discussions：3.3 Possible Types of Tagger • Imitating Tagger: these taggers have recently discovered tagging and are not yet sure about its use, so they simply follow others. It seems that most people will go through this stage and will probably evolve into one of the next two types of taggers, or abandon tagging. • Serious Tagger: these taggers act more like professional cataloger or indexer when they tag. They rationally create and make use of tags for information organization and retrieval by establishing certain rules (either consciously or unconsciously) and with a long-range approach (such as better define their Category tags). • Playful Tagger: these taggers think of tagging as a random and fun thing to do rather than a formal way to categorize one’s information, and are less concerned with tag quality.

36. Conclusion：1. Similarities with Western Taggers • In general, Chinese users exhibit similar usage patterns of social tagging system as Western users. The same regularities in user activity, tag frequencies, kinds of tags used, a stability in the relative proportions of tags for a given tagged resource are found. • Most people use tagging for Personal Information Management, but tags also help them find things they have interests in.

37. Conclusion：2. Differences with Western Taggers • Comparatively, when Chinese people tag, they tend to be more “conservative” and conventional for their preference of terms and kinds of tags to use, and they consider self-expression in tagging less important for them. This may be attributed to culture differences and the Internet censorship in China: • Individualism is not highly deemed in Chinese culture and personal opinions and self-expression are less appreciated. With a collectivistic mind, people are more concerned about the effects of unconventional action and self-presentation. Being unique to draw attention is more likely to be seen as “showing off” than “being cool”. • Under the government’s Internet censorship and surveillance system, the Great Firewall of China, people would be rather cautious with their online activities. • Taggers that create highly personalized tags do exists, only that they are not the minority.

38. Future Work: • How can system better support different types of tagger? System support of tagging could become offensive because too much machine interference may abuse the individuality and “democratic” nature of tagging. The environment that tagging takes place would be an important factor for the design of system support. • What can catalogers or indexers learn from social tagging practices for future organization of information services? “Traditional taggers” (librarians, indexers, etc) may benefit by looking at the social tagging practices of their patrons. It has been recognized that the distance between the standard language and public popular language, or the semantic gap, will impede resource discovery and hence the degree that audiences engage with the information repository. So social tagging and folksonomy could be helpful to gain a better understanding of user’s perceptions of the information domain, by offering an opportunity for the institutions to connect with individuals. Of course, it will be ridiculous to observe the highly divergent Del.icio.us users, but enterprises or organizations with specific user groups may find this approach worth taking.

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