Ninkov, A.; Vaughan, L.: ¬A webometric analysis of the online vaccination debate (2017)
0.01
0.0050440403 = product of:
0.020176161 = sum of:
0.020176161 = product of:
0.040352322 = sum of:
0.040352322 = weight(_text_:methods in 3605) [ClassicSimilarity], result of:
0.040352322 = score(doc=3605,freq=2.0), product of:
0.18168657 = queryWeight, product of:
4.0204134 = idf(docFreq=2156, maxDocs=44218)
0.045191016 = queryNorm
0.22209854 = fieldWeight in 3605, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.0204134 = idf(docFreq=2156, maxDocs=44218)
0.0390625 = fieldNorm(doc=3605)
0.5 = coord(1/2)
0.25 = coord(1/4)
- Abstract
- Webometrics research methods can be effectively used to measure and analyze information on the web. One topic discussed vehemently online that could benefit from this type of analysis is vaccines. We carried out a study analyzing the web presence of both sides of this debate. We collected a variety of webometric data and analyzed the data both quantitatively and qualitatively. The study found far more anti- than pro-vaccine web domains. The anti and pro sides had similar web visibility as measured by the number of links coming from general websites and Tweets. However, the links to the pro domains were of higher quality measured by PageRank scores. The result from the qualitative content analysis confirmed this finding. The analysis of site ages revealed that the battle between the two sides had a long history and is still ongoing. The web scene was polarized with either pro or anti views and little neutral ground. The study suggests ways that professional information can be promoted more effectively on the web. The study demonstrates that webometrics analysis is effective in studying online information dissemination. This kind of analysis can be used to study not only health information but other information as well.
