Search (2 results, page 1 of 1)

  • × author_ss:"Golbeck, J."
  • × theme_ss:"Internet"
  1. Golbeck, J.; Grimes, J.M.; Rogers, A.: Twitter use by the U.S. Congress (2010) 0.00
    0.002269176 = product of:
      0.004538352 = sum of:
        0.004538352 = product of:
          0.009076704 = sum of:
            0.009076704 = weight(_text_:a in 3703) [ClassicSimilarity], result of:
              0.009076704 = score(doc=3703,freq=10.0), product of:
                0.053105544 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046056706 = queryNorm
                0.1709182 = fieldWeight in 3703, product of:
                  3.1622777 = tf(freq=10.0), with freq of:
                    10.0 = termFreq=10.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3703)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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
    0.0020296127 = product of:
      0.0040592253 = sum of:
        0.0040592253 = product of:
          0.008118451 = sum of:
            0.008118451 = weight(_text_:a in 408) [ClassicSimilarity], result of:
              0.008118451 = score(doc=408,freq=8.0), product of:
                0.053105544 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046056706 = queryNorm
                0.15287387 = fieldWeight in 408, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046875 = fieldNorm(doc=408)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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