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Antin, J.; Earp, M.: With a little help from my friends : self-interested and prosocial behavior on MySpace Music (2010)
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- Abstract
- In this article, we explore the dynamics of prosocial and self-interested behavior among musicians on MySpace Music. MySpace Music is an important platform for social interactions and at the same time provides musicians with the opportunity for significant profit. We argue that these forces can be in tension with each other, encouraging musicians to make strategic choices about using MySpace to promote their own or others' rewards. We look for evidence of self-interested and prosocial friending strategies in the social network created by Top Friends links. We find strong evidence that individual preferences for prosocial and self-interested behavior influence friending strategies. Furthermore, our data illustrate a robust relationship between increased prominence and increased attention to others' rewards. These results shed light on how musicians manage their interactions in complex online environments and extend research on social values by demonstrating consistent preferences for prosocial or self-interested behavior in a multifaceted online setting.
-
Thelwall, M.; Buckley, K.: Topic-based sentiment analysis for the social web : the role of mood and issue-related words (2013)
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- Abstract
- General sentiment analysis for the social web has become increasingly useful for shedding light on the role of emotion in online communication and offline events in both academic research and data journalism. Nevertheless, existing general-purpose social web sentiment analysis algorithms may not be optimal for texts focussed around specific topics. This article introduces 2 new methods, mood setting and lexicon extension, to improve the accuracy of topic-specific lexical sentiment strength detection for the social web. Mood setting allows the topic mood to determine the default polarity for ostensibly neutral expressive text. Topic-specific lexicon extension involves adding topic-specific words to the default general sentiment lexicon. Experiments with 8 data sets show that both methods can improve sentiment analysis performance in corpora and are recommended when the topic focus is tightest.
-
Mesgari, M.; Okoli, C.; Mehdi, M.; Nielsen, F.A.; Lanamäki, A.: ¬"The sum of all human knowledge" : a systematic review of scholarly research on the content of Wikipedia (2015)
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- Abstract
- Wikipedia may be the best-developed attempt thus far to gather all human knowledge in one place. Its accomplishments in this regard have made it a point of inquiry for researchers from different fields of knowledge. A decade of research has thrown light on many aspects of the Wikipedia community, its processes, and its content. However, due to the variety of fields inquiring about Wikipedia and the limited synthesis of the extensive research, there is little consensus on many aspects of Wikipedia's content as an encyclopedic collection of human knowledge. This study addresses the issue by systematically reviewing 110 peer-reviewed publications on Wikipedia content, summarizing the current findings, and highlighting the major research trends. Two major streams of research are identified: the quality of Wikipedia content (including comprehensiveness, currency, readability, and reliability) and the size of Wikipedia. Moreover, we present the key research trends in terms of the domains of inquiry, research design, data source, and data gathering methods. This review synthesizes scholarly understanding of Wikipedia content and paves the way for future studies.
-
Elsweiler, D.; Harvey, M.: Engaging and maintaining a sense of being informed : understanding the tasks motivating twitter search (2015)
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- Abstract
- Micro-blogging services such as Twitter represent constantly evolving, user-generated sources of information. Previous studies show that users search such content regularly but are often dissatisfied with current search facilities. We argue that an enhanced understanding of the motivations for search would aid the design of improved search systems, better reflecting what people need. Building on previous research, we present qualitative analyses of two sources of data regarding how and why people search Twitter. The first, a diary study (p?=?68), provides descriptions of Twitter information needs (n?=?117) and important meta-data from active study participants. The second data set was established by collecting first-person descriptions of search behavior (n?=?388) tweeted by twitter users themselves (p?=?381) and complements the first data set by providing similar descriptions from a more plentiful source. The results of our analyses reveal numerous characteristics of Twitter search that differentiate it from more commonly studied search domains, such as web search. The findings also shed light on some of the difficulties users encounter. By highlighting examples that go beyond those previously published, this article adds to the understanding of how and why people search such content. Based on these new insights, we conclude with a discussion of possible design implications for search systems that index micro-blogging content.
-
Zhitomirsky-Geffet, M.; Bratspiess, Y.: Professional information disclosure on social networks : the case of Facebook and LinkedIn in Israel (2016)
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- Abstract
- Disclosure of personal information on social networks has been extensively researched in recent years from different perspectives, including the influence of demographic, personality, and social parameters on the extent and type of disclosure. However, although some of the most widespread uses of these networks nowadays are for professional, academic, and business purposes, a thorough investigation of professional information disclosure is still needed. This study's primary aim, therefore, is to conduct a systematic and comprehensive investigation into patterns of professional information disclosure and various factors involved on different types of social networks. To this end, a user survey was conducted. We focused specifically on Facebook and LinkedIn, the 2 diverse networks most widely used in Israel. Significant differences were found between these networks. For example, we found that on Facebook professional pride is a factor in professional information disclosure, whereas on LinkedIn, work seniority and income have a significant effect. Thus, our findings shed light on the attitudes and professional behavior of network members, leading to recommendations regarding advertising strategies and network-appropriate self-presentation, as well as approaches that companies might adopt according to the type of manpower required.
-
Schultz, S.: ¬Die eine App für alles : Mobile Zukunft in China (2016)
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- Date
- 22. 6.2018 14:22:02
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Landwehr, A.: China schafft digitales Punktesystem für den "besseren" Menschen (2018)
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- Date
- 22. 6.2018 14:29:46
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Andrade, T.C.; Dodebei, V.: Traces of digitized newspapers and bom-digital news sites : a trail to the memory on the internet (2016)
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- Date
- 19. 1.2019 17:42:22
-
Social Media und Web Science : das Web als Lebensraum, Düsseldorf, 22. - 23. März 2012, Proceedings, hrsg. von Marlies Ockenfeld, Isabella Peters und Katrin Weller. DGI, Frankfurt am Main 2012 (2012)
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-
Oguz, F.; Koehler, W.: URL decay at year 20 : a research note (2016)
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- Date
- 22. 1.2016 14:37:14
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Hartmann, B.: Ab ins MoMA : zum virtuellen Museumsgang (2011)
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- Date
- 3. 5.1997 8:44:22
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Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment in Twitter events (2011)
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- Date
- 22. 1.2011 14:27:06
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Okoli, C.; Mehdi, M.; Mesgari, M.; Nielsen, F.A.; Lanamäki, A.: Wikipedia in the eyes of its beholders : a systematic review of scholarly research on Wikipedia readers and readership (2014)
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- Date
- 18.11.2014 13:22:03
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Firnkes, M.: Schöne neue Welt : der Content der Zukunft wird von Algorithmen bestimmt (2015)
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- Date
- 5. 7.2015 22:02:31
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Egbert, J.; Biber, D.; Davies, M.: Developing a bottom-up, user-based method of web register classification (2015)
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- 4. 8.2015 19:22:04
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Evans, H.K.; Ovalle, J.; Green, S.: Rockin' robins : do congresswomen rule the roost in the Twittersphere? (2016)
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- Date
- 22. 1.2016 11:51:19
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Arbelaitz, O.; Martínez-Otzeta. J.M.; Muguerza, J.: User modeling in a social network for cognitively disabled people (2016)
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- 22. 1.2016 12:02:26
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Dufour, C.; Bartlett, J.C.; Toms, E.G.: Understanding how webcasts are used as sources of information (2011)
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- 22. 1.2011 14:16:14
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Zimmer, M.; Proferes, N.J.: ¬A topology of Twitter research : disciplines, methods, and ethics (2014)
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- 20. 1.2015 18:30:22
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Bhattacharya, S.; Yang, C.; Srinivasan, P.; Boynton, B.: Perceptions of presidential candidates' personalities in twitter (2016)
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- Date
- 22. 1.2016 11:25:47
