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					Opinions on the use and value of social tagging
Lorraine F. Normore
University of Tennessee, School of Information Sciences, Knoxville, TN (37996)

Brandy N. Blaylock
University of Tennessee, School of Information Sciences, Knoxville, TN (37996)

The use of social tagging as a mechanism for enhancing access to information on social
networking site s ha s been widely discussed. Thi s study explores thi s i ssue by examining
the views of students in two introductory informa tion organization classe s on participation
in social networks, tag generation and the value of tagging.

Incoming students in information science programs provide researchers with the special
opportunity of seeing the development of ideas around the use and value of bibliographic
control from the context of views based in existing societal norms. In classes in
information organization, they are taught the approaches that libraries and other
information agencies have taken concerning the generation of descriptive practice. They
are also confronted with other approaches toward description as they learn about the
social networks associated with Web 2.0, both in class and in their home environments.
In thinking about the role of social tagging in description, these students are in the almost
unique position of seeing the issues “from both sides now”. This study looked into the
awareness of social networking sites and social tagging among two groups of information
science students. It analyzed the content of discussion boards on this topic, looking also
at reports on tag generation and the evaluation of tags as a way to locate content.

Social tagging
Traditional information systems regularize the variety of names associated with concepts
and bring together content related to the same information objects by adopting controlled
vocabularies. While controlled vocabularies are quite effective in bringing information
on a given topic together, it is generally agreed that they have a number of flaws. Users
have to know the “preferred term” or they have to know to look up the preferred term in
an authority source like a thesaurus. Controlled vocabularies often use less cur rent
terminology than that used in common speech and they are often quite formal. To
overcome these deficiencies, a recent trend in online communities is to use what is
sometimes referred to a social tagging. Giving readers the capability of generating “tags”
or labels for content, it is believed, provides access to content without the need to learn a
complex nomenclature (Peterson, 2006; Hammond et al., 2005).

The benefits of folksonomic “tagging” are hotly debated. The popularity of
shared/community information sites such as del.icio.us, flickr, youtube, and technorati
has opened a door, allowing people to both create and share digital material and to
describe them using their own terminology (Rainie, 2007). While this approach is very
popular at this time, a number of papers have isolated and discussed issues around the
quality of tags produced in folksonomies (Peterson, 2006; Guy & Tonkin, 2006) and
about the long-term viability of such practices (Rosenfeld, 2005).

Tag generation
One aspect of this debate concerns differences among the parties responsible for
generating the terminology used to support information access and the intent that each
bring to the process of index generation. Rafferty and Hidderley (2007) provide an
interesting analysis of index generation that provides insight into this matter. They
distinguish expert- led, author-generated, and user-oriented indexing. Expert- led
approaches, they suggest, are directed from authoritative sources to a user audience.
While the nature of the controlled vocabularies used may privilege certain worldviews,
they also enable the construction of knowledge maps, which themselves can provide
pathways through groups of documents. Author-based indexing, it is argued, uses terms
that are community-based, since the authors themselves are rooted in those communities.
However, it focuses on the interpretation of the work as seen by the author, and not
necessarily as it is seen by the audience. The third alternative discussed by Rafferty and
Hidderley is user-based indexing. A by-product of the move towards social software,
social tagging produces metadata characterized by yet another set of features, namely a
closer match to the vocabulary of its potential users.

Rafferty and Hidderley’s analysis brings to the forefront the issue of the intentionality
and directionality of the tag generation process. Expert- led indexing is intended to serve
a user audience by regularizing and systematizing access. Author-based indexing’s intent
is more solipsistic. Its product reflects the worldview of the content generator. Social
tagging, by its very label, implies that this approach to metadata generation is more
community oriented, the word “social” being derived from the Latin “socius” or “friend”.
We ask, however, is whether or not this true. Is social tagging truly social? Do those
who generate tags intend them as a way to communicate with others or do they, too, have
a more solipsistic intent. This issue is beginning to be addressed by a number of
researchers. Graham and Abbas (2007) studied in situ tagging behavior at an ASIS&T
conference poster session to identify issues of tagger motivation. A panel presentation at
the same conference (Tonkin et al., 2008) provided a series of views into the use o f social
tagging in a variety of online community environments. But the question of community
influence on tagging behavior is still open. It is one of the topics of interest to this

Social network use
While teens and young adults have been and continue to be heavy users of the internet
and new online technologies, the number of adult internet users has increased greatly
over the past ten years. Compared with teens and Generation Y (ages 18-32), Jones and
Fox (2009) show that older generations are more likely to use the internet for information
seeking and exchange and somewhat less for socializing and entertainment. In a parallel
manner to the growth of internet use, social network sites have also attracted an
increasing proportion of adult users. Lenhart (2009) provides data that shows that the
share of adult users who have profiles on social networking sites has quadrupled over the
past four years. Like teens, adults tend to use these sites for personal rather than
professional purposes, reaching out to friends and acquaintances. Unlike teens, however,
adults are more likely to have privacy concerns and are more likely to restrict access to
their content. The students in this study come from both Generation Y and adults above
32. In both study years, 2007 and 2008, the average age of our students was 33, with
roughly comparable ranges (2007: 22-59; 2008: 21-54). Their opinions will be of
particular interest from this perspective as well.
Data Gathering Methodology
To best gauge the attitudes and usage of social tagging within an information science
context, we collected data from students in an introductory Master’s level course on
information representation and organization taught by the first researcher. Social tagging
was discussed in the context of subject description. Data was collected from a required
discussion board, timed to take place in the period in which the related topic was
introduced in class. Data was collected from two classes on two consecutive Fall terms,
2007 and 2008. The 2007 group consisted of 28 students and the 2008 group consisted of
24, for a total of 52 participants. The students were asked to discuss their experiences and
opinions about social tagging on an online discussion board using the course content site
on Blackboard. The exact assignment read like this:

       “You're asked to discuss your experiences with social tagging on sites like
       del.icio.us, flickr, youtube or technorati. If you have not tried out this feature of
       the social networking sites, do you think that people will be able to create useful
       keywords to help others find information they're interested in on these sites?
       Consider trying out one of these sites and reporting back on your experience.”

Responses varied in length from a single sentence to paragraphs of multiple sentences.
Although each student was required to create two postings to the discussion board for
class credit, they were allowed to post as many times as they wished.

Data Analysis
All posts from the discussion boards for both classes were collected. This resulted in 138
posts. In reporting on questions related to the experiences of the individ ual participants
concerning either prior exposure to social networking sites or to tag generation, the unit
of analysis was the speaker, with all responses considered as contributors to the correct
coding of the individual. For issues related to the evaluation of tagging, the unit of
analysis was the individual post. These were labeled by speaker and the number of the
post authored by that participant. For example, the first post by Speaker 1 was labeled
Sp1.1; the second post by Speaker 1 was labeled Sp1.2 and so on.

Content analysis was done for each entry to evaluate the posts on various factors such as
past experience with social tagging sites and positive or negative feelings towards social
tagging. Data was assigned to the categories that follow:
1. Those who report prior experience with social networking sites, with or without
2. Those who report no experience with social networking sites or who tried these sites
    for the related class discussion board
3. Those who report they generate tags (no attribution as to who the tags are for)
4. Those who report that they generate tags for themselves
5. Those who report they generate tags for others
6. Those of positive/favorable reports on tagging
7. Those of “issue”/ reports for tagging

Each post was read with these criteria in mind and cited accordingly when a subject’s
remarks seemed to qualify for the criteria. All posts were independently analyzed by
both researchers and their codings were compared, differences analyzed, and the resulting
decisions reported in this study. If the post did not contain information that supported
inclusion in a category grouping (e.g., no information on experience with social
networking sites), it was not included in the analysis below. If a post contained
comments that showed both the benefits of tagging and problems associated with tagging,
it was in included in both counts.

Table 1 shows how the number of study participants in each year compared in their prior
experience with social networking sites.

Table 1. The relationship between experience with social networking sites and class
Experience with social networking sites 2007 2008 Total
Prior experience                         20    16      36
No prior experience                      7     5       12
 or only for this assignment
Total                                    27    21      48

The table shows only a small amount of differentiation between the two classes in their
reported prior exposure rates to social networking sites, given the differing numbers of
students in their respective classes. The proportion of student with prior experience in
the 2007 class is 20/28 or .71; the proportion in 2008 is 16/24 or .67.

There were unfortunately, from our perspective, only a small number of reports on the
tagging behavior of these students. These are shown in Table 2.

Table 2. The relationship between the targets of tagging behavior and class year.
Attributed target of tagging behavior 2007 2008 Total
Generate tags for themselves          6       2       8
Generate tags for the use of others   1       4       5
No attribution                        1       0       1
Total                                 8       6       14

While this data is relatively sparse, it does not provide evidence against the hypothesis
that tagging is as likely intended for the use of the tagger as it is for the good of the social
networking community in which it is used. There is some suggestion that the groups
differ in their tendencies to use tags for personal use rather than for their community but
there is too little data to support any conclusion.
Table 3 shows the distribution of responses that were coded either positively or in favor
of tagging compared to the number that discussed issues or problems associated with
socially generated tags. Further, it shows the distribution of those responses across the
two class years in the study.

Table 3. Reports on the value of tags in a social networking context.
Reports of the values of tags 2007 2008 Total
Positive/favorable            15      26      41
Issues/problems               42      27      69
Total                         57      53      110

These data show the greatest difference in the data collected in this study. The 2007 class
data shows a predisposition to see the use of social tagging as problematic. By
comparison, the 2008 class’s comments were almost perfectly balanced between positive
and negative reports on the value of social tagging.

This relatively small study provides a window onto the opinions of two sets of incoming
information science students who are being introduced into the formal study of
bibliographic description. Their backgrounds are relatively comparable--they are
approximately the same average age and share a common introduction to the topic (same
School, same instructor, same textbook). According to Table 1, they do not differ greatly
in the degrees of experience they have had with social netwo rking sites.

They do appear to differ in a substantial way in their attitudes about the benefits of and/or
problems with social tagging in the context of social networking sites. The 2007 class
was almost three times more likely to report issues or problems with social tags as they
were to report favorably on their use. The 2008 class, on the other hand, was almost
equally positive and negative about the use of social tagging.

The locus of this effect is unknown. It may be chance variation between these two groups
of people. Alternatively, it may be due to the increasing societal visibility of social
tagging, as manifest in the growth of use of social networking sites shown in the Lenhard
(2009) study. This would be in line with the observed change in focus from self-oriented
tags to socially oriented tags that we see in the data in Table 2. If collaborative tagging is
to become more broadly engaged in, it could be the result of the growth of positive
feelings about its benefits. An analysis of the specific comments in the positive and
negative reports may provide greater insight into attitudes towards controlled
vocabularies and social tagging. This will be the focus of the next stage of this
investigation. Other issues remain open. The intentionality underlying tag generation is
of particular interest. However, experience gained in this study suggests that this will
require a more direct investigation.
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