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

Understanding coronavirus disease 2019 (COVID-19) vaccine hesitancy: Evidence from the community-driven knowledge site Quora

Objective

The present study aims to examine the threshold of coronavirus disease 2019 (COVID-19) vaccine hesitancy over time and public discourse around COVID-19 vaccination hesitancy.

Methods

We collected 3,952 questions and 66,820 answers regarding COVID-19 vaccination posted on the social question-and-answer website Quora between June 2020 and June 2021 and employed Word2Vec and Sentiment Analysis to analyze the data. To examine changes in the perceptions and hesitancy about the COVID-19 vaccine, we segmented the data into 25 bi-weekly sections.

Results

As positive sentiment about vaccination increased, the number of new vaccinations in the United States also increased until it reached a ceiling point. The vaccine hesitancy phase was identified by the decrease in positive sentiment from its highest peak. Words that occurred only when the positive answer rate peaked (e.g., safe, plan, best, able, help) helped explain factors associated with positive perceptions toward vaccines, and the words that occurred only when the negative answer rate peaked (e.g., early, variant, scientists, mutations, effectiveness) suggested factors associated with vaccine hesitancy. We also identified a period of vaccine resistance, where people who decided not to be vaccinated were unlikely to be vaccinated without further enforcement or incentive.

Conclusions

Findings suggest that vaccine hesitancy occurred because concerns about vaccine safety were high due to a perceived lack of scientific evidence and public trust in healthcare authorities has been seriously undermined. Considering that vaccine-related conspiracy theories and fake news prevailed in the absence of reliable information sources, restoring public trust in healthcare leaders will be critical for future vaccination efforts.

Sports Information Needs in Chinese Online Q&A Community: Topic Mining Based on BERT

The online Question and Answering (Q&A) community has grown globally, allowing users to ask, discuss, and answer questions based on shared interests. As a gathering place for people’s knowledge production, collaboration, and dissemination in the current Internet scene, the online Q&A community can intuitively reflect the public’s information needs and behavior. It also collects many sports-related data and becomes an effective vehicle for comprehending mass sports information needs and disseminating sports knowledge. However, sports-related studies on the online Q&A community have rarely been reported. This study took the sports information in Zhihu, the largest Q&A community in China, as the research object to explore the public needs for sports information in China. We introduced the BERT model through a self-compiled python program and collected 391,092 sports-topic answers in the online Q&A community of Zhihu. Then, we explored the topic content, evolution trend, and user attributes of these answers. We found that the overall trend of sports information needs in Zhihu can be divided into three cycles: the London 2012 Olympic period, the Rio 2016 Olympic period, and the Tokyo 2020 Olympic period in general. The diversified content of information needs included 40 second-level themes and eight first-level themes. Male and female users had similarities and differences in sports information needs. The male and female users had the same information needs for fitness-related information. However, men were more concerned with confrontational solid sports such as basketball and football; women were more likely to care about weight loss, shape effect, and self-protection while doing sports activities. In addition, compared with men, women preferred to emphasize their gender attributes when expressing their needs for sports information to obtain more practical knowledge. In conclusion, our finding reveals that the sports community formed by the current online Q&A community in China is still a male-dominated information field.

Media system dependency and user attachment in social Q&A communities: do active users and lurkers differ?

Purpose

This study aims at exploring users' motives to form attachments within the social Q&A community context and identifying the differences between active users and lurkers when building emotional attachments. By utilizing the media system dependency (MSD) theory, this study investigates into the driving factors of dependency relations (understanding, orientation and play) to user attachments (i.e. attachment to the social Q&A community, attachment to content creators).

Design/methodology/approach

The research model is empirically validated by an online questionnaire among users of a social Q&A community. Deriving from the actual behavioral data, the authors divide 262 valid responses into 157 active users and 105 lurkers according to whether they post or not. The partial least squares (PLS) method is exploited to analyze the relationships in the model. In addition, the PLS-based multi-group analysis is conducted for comparing active users and lurkers.

Findings

The empirical results confirm that dependency relations (understanding, orientation and play) significantly influence user attachments. Multi-group analysis suggests that the effect of understanding dependency relations on attachment to content creators is stronger for active users than for lurkers. However, the effect of orientation dependency relations on user attachment is significant for lurkers but not significant for active users.

Originality/value

This study enriches the knowledge of the MSD theory by extending it to the social Q&A community setting. Based on the MSD theory, the relationships between three sides of dependency relations and two types of user attachments are hypothesized in the research model. Besides, the impact of user heterogeneity in building user emotional attachment still lacks consideration. This study is one of the first in the field of comparison studies to compare active users and lurkers in such context, providing a novel contribution in understanding the motivations and emotional responses of different users.

Evidence of Climate Change Engagement Behaviour on a Facebook Fan-Based Page

Climate change has become one of the most debated topics in recent times. The social media platforms have given the general public the power and propensity to share and express concerns about climate change. However, climate change awareness created on social media depends on user engagement with the contents modulated by emotions. Much has been researched in this area using Twitter, but Facebook fan-based pages have not been extensively explored in the past. In this study, we investigate the engagement behaviour of users on a Facebook fan-based page titled “Global Climate Change Awareness” by analysing user insights data for two years starting from April 2018 to April 2020. Results show that the frequency of posts made to the page did not significantly promote engagement but improved visibility of the contents to the users. Overall, fan growth was attributed more to increased post visibility that enhanced post engagement. Hashtags associated with climate change had a significant reach amongst users, but those associated with disasters where the page expressed sadness and informed users about taking precautions had the highest engagement rate. Likewise, users from developing countries, especially from the small islands, were more engaged with climate change awareness. This study did not assess negative responses from users (possible deniers of climate change) and other Facebook fan-based pages due to data privacy and stringent Facebook policy.

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

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.