Climate Change Communication in an Online Q&amp;A Community: A Case Study of Quora

Jiang, Hanchen; Qiang, Maoshan; Zhang, Dongcheng; Wen, Quan; Xia, Bingqing; An, Nan

doi:10.3390/su10051509

Cited by 15 publications

(13 citation statements)

References 56 publications

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“…Big data analyses have indicated that when interpreting climate events, individuals' preference for frameworks was influenced by demographics [5] and social-political background [2]. Different choices of frameworks can evoke different psychological processes [30], promote or inhibit engagement intentions [31], or gain approval on various levels [32].…”

Section: Climate Change Global Warming and Framesmentioning

confidence: 99%

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#Climatechange vs. #Globalwarming: Characterizing Two Competing Climate Discourses on Twitter with Semantic Network and Temporal Analyses

Shi

Pei-nan

et al. 2020

IJERPH

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Distinct perceptions of the global climate is one of the factors preventing society from achieving consensus or taking collaborative actions on this issue. The public has not even reached an agreement on the naming of the global concern, showing preference for either “climate change” or “global warming”, and few previous studies have addressed these two competing discourses resulting from distinct climate concerns by differently linking numerous climate concepts. Based on the 6,662,478 tweets containing #climatechange or #globalwarming generated between 1 January 2009 and 31 December 2018, we constructed the semantic networks of the two discourses and examined their evolution over the decade. The findings indicate that climate change demonstrated a more scientific perspective and showed an attempt to condense climate discussions rather than diffuse the topic by frequently addressing sub-topics simultaneously. Global warming triggered more political responses and showed a greater connection with phenomena. Temporal analysis suggests that traditional political discussions were gradually fading in both discourses but more recently started to revive in the form of discourse alliance in the climate change discourse. The associations between global warming and weather abnormalitiessuddenly strengthened around 2012. Climate change is becoming more dominant than global warming in public discussions. Although two discourses have shown more similarities in the rank order of important climate concepts, apparent disagreements continue about how these concepts are associated. These findings lay the groundwork for researchers and communicators to narrow the discrepancy between diverse climate perceptions.

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Section: Climate Change Global Warming and Framesmentioning

confidence: 99%

“…There are many other words in tweets besides hashtags to express the author's intention. Multiple approaches, such as LDA and STM [32,73], can help to extract topics from unstructured texts. But in this study, targeting on hashtags is more in line with our research question.…”

Section: Hashtags As Frame Vehicles On Social Mediamentioning

confidence: 99%

#Climatechange vs. #Globalwarming: Characterizing Two Competing Climate Discourses on Twitter with Semantic Network and Temporal Analyses

Shi

Pei-nan

et al. 2020

IJERPH

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“…However, the question-and-answer systems used to solve assignments for a particular course are very rare. As a result, an intelligent question-and-answer system has been developed that returns answers to users' questions according to the principles of a course based course [3] [19]. In this article, we introduce how open vocabulary fits in natural language processing along with machine learning can be used to infer a person's personality from their language use in a hiring interview.…”

Section: Related Workmentioning

confidence: 99%

AN EFFICIENT NOVEL APPROACH FOR SOCIETAL COMMUNICATION OF Q&A COMMUNITY SYSTEM USING TOPIC MODELING TECHNIQUES

P¹

2021

ITII

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The emerging trend in technical research is to use customer-generated data collected by community media to probe community opinion and scientific communication on employment and care issues. This review of the collected data, the launch of a question-and-answer social website, is a separate stack for exploring the key factors that influence public preferences for technical knowledge and opinions. by means of a web search engine, topic modeling, and regression data modeling, this study quantified the effect of the response textual and auxiliary functions on the number of votes received with the response. Compared to previous studies based on open estimates, the model results show that Quora users are more likely to only talk about technology. It can fail when the keywords in the query do not match the text content of large documents that contain relevant questions of existing methods, ie. CNNMF and NMF, as well as some restrictions are not enough. Also, users are often not experts and provide ambiguous queries leading to mixed results and encountering problems with existing methods. To address this problem, in this article we propose a Hadoop model, distributed using semantics, non-negative matrix factorization (HDiSANNMF), to find topics for short texts. It effectively incorporates the semantic correlations of the word context into the model, where the semantic connections between words and their context are learned by omitting the grammatical view of the corpus. The researchers are trying to reorganize the main results and present modern techniques for modeling distributed themes to address technologies and platforms with increasing attributes, as well as how much time and space it takes to generate the model. This document briefly describes the structure of public questions and answers around the world and tracks the development of the main topics Housing and employment opportunities for next generation technologies in the world in real time.

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“…However, blog owners that deny or downplay global warming attempted to disregard the overwhelming scientific evidence, such as Arctic sea‐ice loss and polar bear vulnerability, to cast doubt on other established ecological consequences of global warming, thereby aggravating the consensus gap (Harvey et al , ). A case study on the question–answer community Quora also suggests that emphasis on specific subjects but not popular knowledge of climate change could draw more public attention on the issue of climate change (Jiang et al , ). Brandt et al .…”

Section: Review Of Previous Work and Analysismentioning

confidence: 99%

Social weather: A review of crowdsourcing‐assisted meteorological knowledge services through social cyberspace

Zhu

Zhang

et al. 2019

Geoscience Data Journal

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Crowdsourcing has significantly motivated the development of meteorological services. Starting from the beginning of 2010s and highly motivating after 2014, crowdsourcing-driven meteorological services have evolved from a single collection and observation of data to the systematic acquisition, analysis and application of these data. In this review, by focusing on papers and databases that have combined crowdsourcing methods to promote or implement meteorological knowledge services, we analysed the relevant literature in three dimensions: data collection, information analysis and meteorological knowledge applications. First, we selected the potential data sources for crowdsourcing and discussed the characteristics of the collected data in four dimensions: consciousness, objectiveness, mobility and multidisciplinary.Second, based on the purpose of these studies and the extent of utilizing data as well as knowledge, we categorize the crowdsourcing-based meteorological analysis into three levels: relationship discovery, knowledge generalization and systemized service. Third, according to the application scenario, we discussed the applications that have already been put into use, and we suggest current challenges and future research directions. These previous studies show that the use of crowdsourcing in social space can expand the coverage as well as enhance the performance of meteorological 62 | ZHU et al.

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Climate Change Communication in an Online Q&A Community: A Case Study of Quora

Cited by 15 publications

References 56 publications

#Climatechange vs. #Globalwarming: Characterizing Two Competing Climate Discourses on Twitter with Semantic Network and Temporal Analyses

#Climatechange vs. #Globalwarming: Characterizing Two Competing Climate Discourses on Twitter with Semantic Network and Temporal Analyses

AN EFFICIENT NOVEL APPROACH FOR SOCIETAL COMMUNICATION OF Q&A COMMUNITY SYSTEM USING TOPIC MODELING TECHNIQUES

Social weather: A review of crowdsourcing‐assisted meteorological knowledge services through social cyberspace

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