2014
DOI: 10.1002/acp.3067
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Verbatim and Semantic Imitation in Indexing Resources on the Web: A Fuzzy‐trace Account of Social Tagging

Abstract: Summary: Social tagging is a widespread phenomenon on the Web allowing users to tag resources, such as photos, by freely chosen labels. Imitation of other users' tagging behavior is deemed to increase the inter-individual consistency of tag assignments. Both verbatim and semantic mechanisms have been proposed where the first case suggests reuse of the exact words and the second reuse of the concept without necessarily the word form. Here, we present a multinomial model of assigning tags that integrates these p… Show more

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Cited by 12 publications
(11 citation statements)
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“…Experiments have shown that a substantial amount of tag assignments can be explained by modeling the strength of memory traces of tags [53]. Hence, given equations 1 and 2 correspond with individual tagging behavior, we assume that their formalism can also be used to predict a user's future tag reuse.…”
Section: Research Questionsmentioning
confidence: 99%
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“…Experiments have shown that a substantial amount of tag assignments can be explained by modeling the strength of memory traces of tags [53]. Hence, given equations 1 and 2 correspond with individual tagging behavior, we assume that their formalism can also be used to predict a user's future tag reuse.…”
Section: Research Questionsmentioning
confidence: 99%
“…For instance, they might add the tag "Paris" as the photo shows the place they recently visited. Understanding the cognitive processes involved can help to predict individual tagging behavior [53] and to model phenomena on the collective level, such as the emergence of stable tag distributions [13]. To make appropriate memory units quickly available, human memory is very adaptive and tunes the activation of its units to statistical regularities of the environment (e.g., [4]): The more useful a memory unit has been and the stronger it is related to the current context (i.e., environmental cues), the higher is its activation level and hence, probability of being retrieved.…”
Section: Introductionmentioning
confidence: 99%
“…In the present context, it describes how easily and continuously diverse ideas can be accessed from memory during information-based ideation (Kerne et al, 2008(Kerne et al, , 2014, i.e., when thinking about search topics to be explored in future queries. Referring to previous work on cognitive effects of social tags on mental structures (e.g., categories and associations; e.g., Fu & Dong, 2012;Seitlinger & Ley, 2012;Seitlinger, Ley, & Albert, 2015), we anticipate a tradeoff between fluency and consistency: when users of a digital curation environment perceive others' tags, these tags leave episodic memory traces (Seitlinger & Ley, 2012;Seitlinger et al, 2015), strengthening previously weak associations to a search topic, in case these traces represent new ideas. Considering research in creative cognition (e.g., Smith, Ward, & Finke, 1995;Ward, 2007), this tag-based cognitive effect should reduce the dominance of pre-existing stereotyped associations and give rise to a broader (mental) fan of equally available ideas around a topic.…”
Section: Introductionmentioning
confidence: 79%
“…Table 2 shows the estimates of the model's intercept and slope and how these estimates change as a function of 'Search Condition'. The small amount of variance explained is not surprising as the probability of reusing tags (that underlies S T ) depends not only on semantic attributes of the resources, but also on mediating cognitive processes (e.g., Fu & Dong, 2012;Seitlinger et al, 2015), which are to some extend specified by the tag recommender's algorithm presented in the article's second part. The present regression model, however, did not capture such cognitive processes because its primary purpose was not to explain a large amount of variance in the individuals' tagging behavior but to determine whether the amount of variance explained by the predictor S W differs between the individual and collaborative condition.…”
Section: Resultsmentioning
confidence: 99%
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