-
Zhang, Y.; Zheng, G.; Yan, H.: Bridging information and communication technology and older adults by social network : an action research in Sichuan, China (2023)
0.02
0.024991414 = product of:
0.07497424 = sum of:
0.07497424 = product of:
0.11246135 = sum of:
0.08267841 = weight(_text_:network in 1089) [ClassicSimilarity], result of:
0.08267841 = score(doc=1089,freq=6.0), product of:
0.19402927 = queryWeight, product of:
4.4533744 = idf(docFreq=1398, maxDocs=44218)
0.043569047 = queryNorm
0.42611307 = fieldWeight in 1089, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
4.4533744 = idf(docFreq=1398, maxDocs=44218)
0.0390625 = fieldNorm(doc=1089)
0.029782942 = weight(_text_:29 in 1089) [ClassicSimilarity], result of:
0.029782942 = score(doc=1089,freq=2.0), product of:
0.15326229 = queryWeight, product of:
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.043569047 = queryNorm
0.19432661 = fieldWeight in 1089, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.0390625 = fieldNorm(doc=1089)
0.6666667 = coord(2/3)
0.33333334 = coord(1/3)
- Abstract
- The extant literature demonstrates that the age-related digital divide prevents older adults from enhancing their quality of life. To bridge this gap and promote active aging, this study explores the interplay between social networks and older adults' use of information and communication technology (ICT). Using an action-oriented field research approach, we offered technical help (29 help sessions) to older adult participants recruited from western China. Then, we conducted content analysis to examine the obtained video, audio, and text data. Our results show that, first, different types of social networks significantly influence older adults' ICT use in terms of digital skills, engagement, and attitudes; however, these effects vary from person to person. In particular, our results highlight the crucial role of a stable and long-term supportive social network in learning and mastering ICT for older residents. Second, technical help facilitates the building and reinforcing of such a social network for the participants. Our study has strong implications in that policymakers can foster the digital inclusion of older people through supportive social networks.
-
Springer, M.: Schwarzer Schwan im Internet (2020)
0.01
0.007942118 = product of:
0.023826351 = sum of:
0.023826351 = product of:
0.07147905 = sum of:
0.07147905 = weight(_text_:29 in 5903) [ClassicSimilarity], result of:
0.07147905 = score(doc=5903,freq=2.0), product of:
0.15326229 = queryWeight, product of:
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.043569047 = queryNorm
0.46638384 = fieldWeight in 5903, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.09375 = fieldNorm(doc=5903)
0.33333334 = coord(1/3)
0.33333334 = coord(1/3)
- Source
- Spektrum der Wissenschaft. 2020, H.7, S.29
-
Zhang, M.; Zhang, Y.: Professional organizations in Twittersphere : an empirical study of U.S. library and information science professional organizations-related Tweets (2020)
0.01
0.007425352 = product of:
0.022276055 = sum of:
0.022276055 = product of:
0.06682816 = sum of:
0.06682816 = weight(_text_:network in 5775) [ClassicSimilarity], result of:
0.06682816 = score(doc=5775,freq=2.0), product of:
0.19402927 = queryWeight, product of:
4.4533744 = idf(docFreq=1398, maxDocs=44218)
0.043569047 = queryNorm
0.3444231 = fieldWeight in 5775, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.4533744 = idf(docFreq=1398, maxDocs=44218)
0.0546875 = fieldNorm(doc=5775)
0.33333334 = coord(1/3)
0.33333334 = coord(1/3)
- Abstract
- Twitter is utilized by many, including professional businesses and organizations; however, there are very few studies on how other entities interact with these organizations in the Twittersphere. This article presents a study that investigates tweets related to 5 major library and information science (LIS) professional organizations in the United States. This study applies a systematic tweets analysis framework, including descriptive analytics, network analytics, and co-word analysis of hashtags. The findings shed light on user engagement with LIS professional organizations and the trending discussion topics on Twitter, which is valuable for enabling more successful social media use and greater influence.
-
Hong, H.; Ye, Q.: Crowd characteristics and crowd wisdom : evidence from an online investment community (2020)
0.01
0.0053038225 = product of:
0.015911467 = sum of:
0.015911467 = product of:
0.047734402 = sum of:
0.047734402 = weight(_text_:network in 5763) [ClassicSimilarity], result of:
0.047734402 = score(doc=5763,freq=2.0), product of:
0.19402927 = queryWeight, product of:
4.4533744 = idf(docFreq=1398, maxDocs=44218)
0.043569047 = queryNorm
0.2460165 = fieldWeight in 5763, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.4533744 = idf(docFreq=1398, maxDocs=44218)
0.0390625 = fieldNorm(doc=5763)
0.33333334 = coord(1/3)
0.33333334 = coord(1/3)
- Abstract
- Fueled by the explosive growth of Web 2.0 and social media, online investment communities have become a popular venue for individual investors to interact with each other. Investor opinions extracted from online investment communities capture "crowd wisdom" and have begun to play an important role in financial markets. Existing research confirms the importance of crowd wisdom in stock predictions, but fails to investigate factors influencing crowd performance (that is, crowd prediction accuracy). In order to help improve crowd performance, our research strives to investigate the impact of crowd characteristics on crowd performance. We conduct an empirical study using a large data set collected from a popular online investment community, StockTwits. Our findings show that experience diversity, participant independence, and network decentralization are all positively related to crowd performance. Furthermore, crowd size moderates the influence of crowd characteristics on crowd performance. From a theoretical perspective, our work enriches extant literature by empirically testing the relationship between crowd characteristics and crowd performance. From a practical perspective, our findings help investors better evaluate social sensors embedded in user-generated stock predictions, based upon which they can make better investment decisions.
-
Schrenk, P.: Gesamtnote 1 für Signal - Telegram-Defizite bei Sicherheit und Privatsphäre : Signal und Telegram im Test (2022)
0.01
0.005247115 = product of:
0.015741345 = sum of:
0.015741345 = product of:
0.047224034 = sum of:
0.047224034 = weight(_text_:22 in 486) [ClassicSimilarity], result of:
0.047224034 = score(doc=486,freq=2.0), product of:
0.15257138 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.043569047 = 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)
0.33333334 = coord(1/3)
0.33333334 = coord(1/3)
- Date
- 22. 1.2022 14:01:14
-
Hubert, M.; Griesbaum, J.; Womser-Hacker, C.: Usability von Browsererweiterungen zum Schutz vor Tracking (2020)
0.00
0.0046329014 = product of:
0.013898704 = sum of:
0.013898704 = product of:
0.041696113 = sum of:
0.041696113 = weight(_text_:29 in 5866) [ClassicSimilarity], result of:
0.041696113 = score(doc=5866,freq=2.0), product of:
0.15326229 = queryWeight, product of:
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.043569047 = queryNorm
0.27205724 = fieldWeight in 5866, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5176873 = idf(docFreq=3565, maxDocs=44218)
0.0546875 = fieldNorm(doc=5866)
0.33333334 = coord(1/3)
0.33333334 = coord(1/3)
- Date
- 11. 7.2020 18:50:29
