| Carbon neutrality has become a hot topic of discussion among countries and has been widely discussed on social media.In recent years,as awareness of the extent and speed of climate change has increased,countries have announced more ambitious climate goals.Terms such as carbon neutrality have become more common.Carbon neutrality refers to achieving net zero carbon emissions by increasing carbon sorption or reducing carbon emissions.Many places have developed their roadmaps to achieve carbon neutrality.For example,the European Commission launched the European Green Deal in 2019,a new growth strategy for the European Union.The basic goal of this policy is to make the EU climate neutral by 2050.China,the world’s largest developing country,has committed to achieve carbon neutrality by 2060 and peak CO2 emissions by 2030 to reduce the greenhouse effect.By 2035,the Finnish government intends to achieve carbon neutrality.The development of low-carbon roadmaps by industry sectors is one of the policy tools to achieve this goal.The government started to develop a low-carbon roadmap in 2019,and industry sectors must state when and how they will achieve carbon neutrality.First,social media provides an effective platform for disseminating carbon neutral related information and advancing environmentally friendly living practices.At the same time,social bots are proliferating on social media platforms and are being used as algorithmic agents to promote or amplify certain views and interact with actors on social media,potentially influencing online discussions,news attention,and even public opinion.Previous research has documented the presence of bot activity and developed detection algorithms.However,how social bots affect the attention of different subjects in mixed media systems remains under-researched.twitter,as an international social platform with a rich user base,is suitable for analyzing the discourse discussions related to the international topic of carbon neutrality.In light of the above,this research question aims to cover both the carbon neutral social bots and the social media platform Twitter.Based on the agenda setting theory,this research firstly uses python crawler to collect the relevant contents on Twitter platform with existing datasets,secondly uses Botometer social bot detection technology to identify and classify the accounts in the collected database and conducts a basic feature analysis on the posting form,retweets,likes,followers and views of different categories.Then,we used R language STM structural topic modeling to classify the content of the collected tweets into topics and analyzed the topic bias of different topics using the posting status as the variable.Finally,this study uses time series analysis to analyze the characteristics of the interactions between social bots,ordinary humans and media users on Twitter.The main findings of this paper are:(1)Firstly,social bots occupy a significant proportion(16.6%)of the mixed social media ecology and show certain anthropomorphic characteristics in communication behavior,avatars,and posting content.Compared to human Twitter users tend to post slightly more retweeted content less original content and quoted content.(2)Each type of user has its advantages and disadvantages when it comes to Twitter engagement.Media tweets tend to generate higher levels of engagement overall,but social bots are more effective at getting retweets.And they have some power to spread the word.(3)In carbon neutral issues bot activity selectively favors certain issues,mainly related to industry business related issues such as carbon offsets,decarbonization of real estate,corporate business consolidation,carbon neutrality in buildings,etc.(4)In some agendas,there is a significant one-way relationship from regular human users to Twitter social bots,and from media users to bots,and human users hardly respond to topics amplified by Twitter bots,while content promotion by social bots may indirectly influence public opinion by shaping media coverage. |
