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  • × author_ss:"Golbeck, J."
  • × language_ss:"e"
  1. Golbeck, J.; Grimes, J.M.; Rogers, A.: Twitter use by the U.S. Congress (2010) 0.00 
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    Abstract
    Twitter is a microblogging and social networking service with millions of members and growing at a tremendous rate. With the buzz surrounding the service have come claims of its ability to transform the way people interact and share information and calls for public figures to start using the service. In this study, we are interested in the type of content that legislators are posting to the service, particularly by members of the United States Congress. We read and analyzed the content of over 6,000 posts from all members of Congress using the site. Our analysis shows that Congresspeople are primarily using Twitter to disperse information, particularly links to news articles about themselves and to their blog posts, and to report on their daily activities. These tend not to provide new insights into government or the legislative process or to improve transparency; rather, they are vehicles for self-promotion. However, Twitter is also facilitating direct communication between Congresspeople and citizens, though this is a less popular activity. We report on our findings and analysis and discuss other uses of Twitter for legislators.
    Type
    a
  2. Gruda, D.; Karanatsiou, D.; Mendhekar, K.; Golbeck, J.; Vakali, A.: I alone can fix it : examining interactions between narcissistic leaders and anxious followers on Twitter using a machine learning approach (2021) 0.00 
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    Abstract
    Due to their confidence and dominance, narcissistic leaders oftentimes can be perceived favorably by followers, in particular during times of uncertainty. In this study, we propose and examine the relationship between narcissistic leaders and followers who are prone to experience uncertainty intensely and frequently in general, namely highly anxious followers. We do so by applying machine learning algorithms to account for personality traits in a large sample of leaders and followers on Twitter. We find that highly anxious followers are more likely to interact with narcissistic leaders in general, and male narcissistic leaders in particular. Finally, we also examined these interactions in the context of highly popular leaders and found that as leaders become more popular, they begin to attract less anxious followers, regardless of leader gender. We interpret and discuss these findings in relation to previous work and outline limitations and future research recommendations based on our approach.
    Type
    a
  3. Golbeck, J.; Auxier, B.; Bickford, A.; Cabrera, L.; McHugh, M.C.; Moore, S.; Hart, J.; Resti, J.; Rogers, A.; Zimmerman, J.: Congressional twitter use revisited on the platform's 10-year anniversary : implications for research evaluation practice (2018) 0.00 
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    Type
    a
  4. Golbeck, J.; Koepfler, J.; Emmerling, B.: ¬An experimental study of social tagging behavior and image content (2011) 0.00 
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    Abstract
    Social tags have become an important tool for improving access to online resources, particularly non-text media. With the dramatic growth of user-generated content, the importance of tags is likely to grow. However, while tagging behavior is well studied, the relationship between tagging behavior and features of the media being tagged is not well understood. In this paper, we examine the relationship between tagging behavior and image type. Through a lab-based study with 51 subjects and an analysis of an online dataset of image tags, we show that there are significant differences in the number, order, and type of tags that users assign based on their past experience with an image, the type of image being tagged, and other image features. We present these results and discuss the significant implications this work has for tag-based search algorithms, tag recommendation systems, and other interface issues.
    Type
    a
  5. Klavans, J.L.; LaPlante, R.; Golbeck, J.: Subject matter categorization of tags applied to digital images from art museums (2014) 0.00 
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    Abstract
    In recent years, cultural heritage institutions have increasingly used social tagging. To better understand the nature of these tags, we analyzed tags assigned to a collection of 100 images of art (provided by the steve.museum project) using subject matter categorization. Our results show that the majority of tags describe the people and objects in the image and are generic in nature. This contradicts prior subject matter analyses of queries, tags, and index terms of other image collections, suggesting that the nature of social tags largely depends on the type of collection and on user needs. This insight may help cultural heritage institutions improve their management and use of tags.
    Type
    a

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