-
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.
-
Schrenk, P.: Gesamtnote 1 für Signal - Telegram-Defizite bei Sicherheit und Privatsphäre : Signal und Telegram im Test (2022)
0.01
0.013991722 = product of:
0.027983444 = sum of:
0.027983444 = product of:
0.055966888 = sum of:
0.055966888 = weight(_text_:22 in 486) [ClassicSimilarity], result of:
0.055966888 = score(doc=486,freq=2.0), product of:
0.18081778 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.05163523 = queryNorm
0.30952093 = fieldWeight in 486, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=486)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Date
- 22. 1.2022 14:01:14
