Ahmed Abdeen Hamed, Alexa A. Ayer, Eric M. Clark, Erin A. Irons, Grant T. Taylor and Asim Zia
The purpose of this paper is to test the hypothesis of whether more complex and emergent hashtags can be sufficient pointers to climate change events. Human-induced climate change…
Abstract
Purpose
The purpose of this paper is to test the hypothesis of whether more complex and emergent hashtags can be sufficient pointers to climate change events. Human-induced climate change is one of this century’s greatest unbalancing forces to have affected our planet. Capturing the public awareness of climate change on Twitter has proven to be significant. In a previous research, it was demonstrated by the authors that public awareness is prominently expressed in the form of hashtags that uses more than one bigram (i.e. a climate change term). The research finding showed that this awareness is expressed by more complex terms (e.g. “climate change”). It was learned that the awareness was dominantly expressed using the hashtag: #ClimateChange.
Design/methodology/approach
The methods demonstrated here use objective computational approaches [i.e. Google’s ranking algorithm and Information Retrieval measures (e.g. TFIDF)] to detect and rank the emerging events.
Findings
The results shows a clear significant evidence for the events signaled using emergent hashtags and how globally influential they are. The research detected the Earth Day, 2015, which was signaled using the hashtag #EarthDay. Clearly, this is a day that is globally observed by the worldwide population.
Originality/value
It was proven that these computational methods eliminate the subjectivity errors associated with humans and provide inexpensive solution for event detection on Twitter. Indeed, the approach used here can also be applicable to other types of event detections, beyond climate change, and surely applicable to other social media platforms that support the use of hashtags (e.g. Facebook). The paper explains, in great detail, the methods and all the numerous events detected.
Details
Keywords
Neal Caren, Kay Jowers and Sarah Gaby
Purpose – We build on prior research of social movement communities (SMCs) to conceptualize a new form of cultural support for activism – the social movement online community…
Abstract
Purpose – We build on prior research of social movement communities (SMCs) to conceptualize a new form of cultural support for activism – the social movement online community (SMOC). We define SMOC as a sustained network of individuals who work to maintain an overlapping set of goals and identities tied to a social movement linked through quasi-public online discussions.
Method – This paper uses extensive data collected from Stormfront, the largest online community of white nationalists, for the period from September 2001 to August 2010 totaling 6,868,674 posts. We systematically analyzed the data to allow for a detailed depiction of SMOCs using keyword tags. We also used Stata 11 to analyze descriptive measures such as persistence of user presence and relation of first post to length of stay.
Findings – Our findings suggest that SMOCs provide a new forum for social movements that produces a unique set of characteristics. Nevertheless, many characteristics of SMOCs are also in line with conventional offline SMCs.
Originality of the paper – This research broadens our understanding of the differences between online and offline SMCs and presents the special case of the SMOC as a way for scholars to conceptualize and study social movements that use the Internet to form their collective identity.
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Forough Rahimi and Farshid Danesh
The main objective of this study is to evaluate the impact of Persian Scientific Papers (PSPs) on Persian Wikipedia by studying Wikipedia's citations to these papers.
Abstract
Purpose
The main objective of this study is to evaluate the impact of Persian Scientific Papers (PSPs) on Persian Wikipedia by studying Wikipedia's citations to these papers.
Design/methodology/approach
The present study is applied research, which has been performed by the web-mining method, such as downloading web pages, extracting information (references), identifying papers, detecting peer-review journals and calculating the frequency rates. The statistical population included 10,000 Persian Wikipedia Pages (PWPs) that were analyzed in two rounds with a six-month interval.
Findings
The number of pages containing the Persian references section was 3,994 and 4,063 out of the 10,000 pages extracted in the first and second rounds. The ratio of pages that cited scientific sources (58 and 67 pages) to the pages extracted from the PWP was equal to 0.58 and 0.67%. The ratio of pages that cited scientific sources to pages with Persian references in each round was equal to 1.45 and 1.64%. The number of references extracted from the PWP in each round equaled 30,441 and 35,891. Eight titles from reputable Persian journals had received at least three citations from Wikipedia.
Originality/value
The present study has determined the extent of interaction between science and society (knowledge flow) in the form of citations from Wikipedia articles to articles in peer-reviewed journals. The study of this issue in Persian Wikipedia in more than 2000 Persian peer-reviewed journals shows the originality of the present paper. Studying citation reliability in a collaborative and openly editable platform is another originality of the work.