Son, J.; Lee, J.; Larsen, I.; Nissenbaum, K.R.; Woo, J.: Understanding the uncertainty of disaster tweets and its effect on retweeting : the perspectives of uncertainty reduction theory and information entropy (2020)
0.01
0.0064978357 = product of:
0.04548485 = sum of:
0.032137483 = weight(_text_:wide in 5962) [ClassicSimilarity], result of:
0.032137483 = score(doc=5962,freq=2.0), product of:
0.1312982 = queryWeight, product of:
4.4307585 = idf(docFreq=1430, maxDocs=44218)
0.029633347 = queryNorm
0.24476713 = fieldWeight in 5962, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.4307585 = idf(docFreq=1430, maxDocs=44218)
0.0390625 = fieldNorm(doc=5962)
0.013347364 = weight(_text_:information in 5962) [ClassicSimilarity], result of:
0.013347364 = score(doc=5962,freq=14.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.256578 = fieldWeight in 5962, product of:
3.7416575 = tf(freq=14.0), with freq of:
14.0 = termFreq=14.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=5962)
0.14285715 = coord(2/14)
- Abstract
- The rapid and wide dissemination of up-to-date, localized information is a central issue during disasters. Being attributed to the original 140-character length, Twitter provides its users with quick-posting and easy-forwarding features that facilitate the timely dissemination of warnings and alerts. However, a concern arises with respect to the terseness of tweets that restricts the amount of information conveyed in a tweet and thus increases a tweet's uncertainty. We tackle such concerns by proposing entropy as a measure for a tweet's uncertainty. Based on the perspectives of Uncertainty Reduction Theory (URT), we theorize that the more uncertain information of a disaster tweet, the higher the entropy, which will lead to a lower retweet count. By leveraging the statistical and predictive analyses, we provide evidence supporting that entropy validly and reliably assesses the uncertainty of a tweet. This study contributes to improving our understanding of information propagation on Twitter during disasters. Academically, we offer a new variable of entropy to measure a tweet's uncertainty, an important factor influencing disaster tweets' retweeting. Entropy plays a critical role to better comprehend URLs and emoticons as a means to convey information. Practically, this research suggests a set of guidelines for effectively crafting disaster messages on Twitter.
- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.10, S.1145-1161
