Search (2 results, page 1 of 1)
- Did you mean:
- lcsh's%3a%22Machine theory%22 2
- lcshs%3a%22Machine theory%22 2
-
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)
0.02
0.017439222 = product of: 0.034878444 = sum of: 0.034878444 = product of: 0.06975689 = sum of: 0.06975689 = weight(_text_:theory in 5962) [ClassicSimilarity], result of: 0.06975689 = score(doc=5962,freq=4.0), product of: 0.21471956 = queryWeight, product of: 4.1583924 = idf(docFreq=1878, maxDocs=44218) 0.05163523 = queryNorm 0.3248744 = fieldWeight in 5962, product of: 2.0 = tf(freq=4.0), with freq of: 4.0 = termFreq=4.0 4.1583924 = idf(docFreq=1878, maxDocs=44218) 0.0390625 = fieldNorm(doc=5962) 0.5 = coord(1/2) 0.5 = coord(1/2)
- 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.
-
Dijk, J: ¬The digital divide (2020)
0.01
0.014797671 = product of: 0.029595342 = sum of: 0.029595342 = product of: 0.059190683 = sum of: 0.059190683 = weight(_text_:theory in 68) [ClassicSimilarity], result of: 0.059190683 = score(doc=68,freq=2.0), product of: 0.21471956 = queryWeight, product of: 4.1583924 = idf(docFreq=1878, maxDocs=44218) 0.05163523 = queryNorm 0.27566507 = fieldWeight in 68, product of: 1.4142135 = tf(freq=2.0), with freq of: 2.0 = termFreq=2.0 4.1583924 = idf(docFreq=1878, maxDocs=44218) 0.046875 = fieldNorm(doc=68) 0.5 = coord(1/2) 0.5 = coord(1/2)
- Content
- What is the digital divide? -- Research and theory of the digital divide -- Motivation and attitude -- Physical access -- Digital and 21st-century skills usage inequality -- Outcomes -- Social and digital inequality -- Solutions to soften the digital divide.
Authors
- Dijk, J 1
- Larsen, I. 1
- Lee, J. 1
- Nissenbaum, K.R. 1
- Son, J. 1
- Woo, J. 1
Subjects
- Computer literacy 1
- Digital divide 1
- Digitale Revolution 1
- Digitale Spaltung 1
- Internet literacy 1
- Medienkompetenz 1
- Soziale Ungleichheit 1
- Sozialer Wandel 1
- Wissenskluft 1
- More… Less…