Why we tag: motivations for annotation in mobile and online media

By Morgan G. Ames, Mor Naaman. International Conference on Human Factors in Computing Systems, 2007

1,000 citations recorded by the source corpus.

Subfields: Computer Science Applications, Computer Vision and Pattern Recognition, Transportation

View Paper: https://www.semanticscholar.org/paper/6c63652393ba01af5bd39a4788413486bef29a2c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Science Applications

In Computer Vision and Pattern Recognition

In Transportation

Citations in the corpus

Personalized Deep Learning for Tag Recommendation (2017, background): “Tags assigned freely by users can be used to support users organizing or searching resources of social media systems [1].”
Placing flickr photos on a map (2009, background): “According to recent literature [2, 21] users spend considerable eﬀort to organise their“memory”geographically by describing photos with tags related to locations where they were taken.”
Exploring place through user-generated content: Using Flickr tags to describe city cores (2010, background): “The motivation behind tagging is generally thought to be twofold; apart from the organization of content for personal means, users of tagging systems are driven by the idea of social contribution and the desire to share with others [2].”
I'm the mayor of my house: examining why people use foursquare - a social-driven location sharing application (2011, background): “We contribute to the research community’s increasing understanding of how and why people use social media (for example, [3, 6, 18, 21]).”
Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr (2013, background): “Ames and Naaman (2007) have studied motivations in tagging.”
A visual analytics approach to understanding cycling behaviour (2012, neutral): “This chapter considers some cinematic responses to the concept of the vacuum in space.”
iPrivacy: Image Privacy Protection by Identifying Sensitive Objects via Deep Multi-Task Learning (2017, neutral): “Compared to them, our approach provides a finer level of image classification and is much more efficient.”
Uses and Gratifications of digital photo sharing on Facebook (2016, neutral): “…photo sharing, such as feedback, public approval, attention, recognition, and social rewards in yje form of comments and consequent conversation on shared photos, have also been frequently highlighted in the literature (Ames & Naaman, 2007; Frohlich et al., 2002; Malinen, 2011; Nov et al., 2010).”
How annotation styles influence content and preferences (2013, background): “Thus, our results focus on the social, organizational, and communicative dimensions of tagging [4]; tagging for the general public was also shown to be the most common motivation for tagging on Flickr [13].”
Sensitive Self-disclosures, Responses, and Social Support on Instagram: The Case of #Depression (2017, background): “Although hashtags can be thought of as a way of categorizing content [1] to make it more findable and analogously more public, we suspect that the existence of ingroup/out-group language (See Figure 1.”
Moving beyond untagging: photo privacy in a tagged world (2010, background): “Several studies have examined the social uses and impact of tagging on Flickr, a photo sharing site that does provide some social networking capabilities [4].”
How flickr helps us make sense of the world: context and content in community-contributed media collections (2007, background): “In particular, due to the complex motivations involved that drive usage of tags and text descriptions [2], tags do not necessesarily describe the content of the image [11].”
Social Cues, Social Biases: Stereotypes in Annotations on People Images (2018, background): “Open annotation, in which contributors describe an image in their own words rather than using a controlled vocabulary, offers the potential to capture what “average people” perceive an image to be or to portray (Ames and Naaman 2007).”
Flickr tag recommendation based on collective knowledge (2008, background): “This aspect is studied thoroughly in [23] [16] [14] [4].”
Youtube traffic characterization: a view from the edge (2007, background): “This shift toward user generated content represents one of the biggest changes of the Web since its inception in the early 1990 s.”