Search (2 results, page 1 of 1)

  • × author_ss:"Zhitomirsky-Geffet, M."
  • × theme_ss:"Internet"
  • × year_i:[2010 TO 2020}
  1. Zhitomirsky-Geffet, M.; Bratspiess, Y.: Professional information disclosure on social networks : the case of Facebook and LinkedIn in Israel (2016) 0.00 
    0.0020714647 = product of:
  0.0041429293 = sum of:
    0.0041429293 = product of:
      0.008285859 = sum of:
        0.008285859 = weight(_text_:a in 2766) [ClassicSimilarity], result of:
          0.008285859 = score(doc=2766,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.15602624 = fieldWeight in 2766, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2766)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    Disclosure of personal information on social networks has been extensively researched in recent years from different perspectives, including the influence of demographic, personality, and social parameters on the extent and type of disclosure. However, although some of the most widespread uses of these networks nowadays are for professional, academic, and business purposes, a thorough investigation of professional information disclosure is still needed. This study's primary aim, therefore, is to conduct a systematic and comprehensive investigation into patterns of professional information disclosure and various factors involved on different types of social networks. To this end, a user survey was conducted. We focused specifically on Facebook and LinkedIn, the 2 diverse networks most widely used in Israel. Significant differences were found between these networks. For example, we found that on Facebook professional pride is a factor in professional information disclosure, whereas on LinkedIn, work seniority and income have a significant effect. Thus, our findings shed light on the attitudes and professional behavior of network members, leading to recommendations regarding advertising strategies and network-appropriate self-presentation, as well as approaches that companies might adopt according to the type of manpower required.
    Type
    a
  2. Bar-Ilan, J.; Zhitomirsky-Geffet, M.; Miller, Y.; Shoham, S.: ¬The effects of background information and social interaction on image tagging (2010) 0.00 
    0.0011959607 = product of:
  0.0023919214 = sum of:
    0.0023919214 = product of:
      0.0047838427 = sum of:
        0.0047838427 = weight(_text_:a in 3453) [ClassicSimilarity], result of:
          0.0047838427 = score(doc=3453,freq=4.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.090081796 = fieldWeight in 3453, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3453)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    In this article, we describe the results of an experiment designed to understand the effects of background information and social interaction on image tagging. The participants in the experiment were asked to tag 12 preselected images of Jewish cultural heritage. The users were partitioned into three groups: the first group saw only the images with no additional information whatsoever, the second group saw the images plus a short, descriptive title, and the third group saw the images, the titles, and the URL of the page in which the image appeared. In the first stage of the experiment, each user tagged the images without seeing the tags provided by the other users. In the second stage, the users saw the tags assigned by others and were encouraged to interact. Results show that after the social interaction phase, the tag sets converged and the popular tags became even more popular. Although in all cases the total number of assigned tags increased after the social interaction phase, the number of distinct tags decreased in most cases. When viewing the image only, in some cases the users were not able to correctly identify what they saw in some of the pictures, but they overcame the initial difficulties after interaction. We conclude from this experiment that social interaction may lead to convergence in tagging and that the wisdom of the crowds helps overcome the difficulties due to the lack of information.
    Type
    a

Authors