Not All Places Are Equal: Using Instagram to Understand Cognitions and Affect towards Renewable Energy Infrastructures

Round 1

Reviewer 1 Report

The "Using Instagram+RET" is novel and may yield interesting research although at present I would suggest it to publish the work after revision. 

"In recent years, social media has become integrated into many aspects o..." This is strong and contentious statement without proof?  

"RETs on Instagram posts?,,," If this is your own conclusion, it is out of place here in same paragraph with statement?  

"...studying public perception of energy technologies" you should motivate why you say that.

"...Sentiment Analysis..." What are the other feasible alternatives?  

"linguistic associations elicited by wind, solar, geothermal energies..." What are the advantages of adopting this particular metric over others in this case?  

"The justice word has also a big frequency in the planet cluster," How will this affect the results? More details should be furnished. 

"there is no strong relations between the Instagram posts, RETs, and planet" it does not clearly follow out of the literature discussion that you have given. 

Moreover, the manuscript could be substantially improved by relying and citing more on recent literatures about real-life case studies on RET such as the followings:

https://doi.org/10.1016/j.seta.2021.101929

https://doi.org/10.1016/j.applthermaleng.2021.116756

Author Response

Reviewer #1:

1. "In recent years, social media has become integrated into many aspects o..." This is strong and contentious statement without proof? 

>>>>>>>>>> Thank you for this comment. After a careful review, we have added this reference to the statement: Li, R., Crowe, J., Leifer, D., Zou, L., & Schoof, J. Beyond big data: Social media challenges and opportunities for understanding social perception of energy. Energy Research & Social Science 2019;56(101217).

 

2. "RETs on Instagram posts?,,," If this is your own conclusion, it is out of place here in same paragraph with statement? 

>>>>>>>>>> While we are not sure we understand the comment correctly, we would like to clarify that this is one of our research questions (which places do people associate with RETs on Instagram posts?), which we derived from the assumptions we discussed in the paper. This question also arises because, despite the importance that social media has for modern discourse; to the authors’ knowledge, no study has yet investigated place-relationships in the context of RETs on social media platforms. We seek to fill this research gap by examining the potential relationship between sentiments articulated in Instagram content related to RETs and places.

 

3. "...studying public perception of energy technologies" you should motivate why you say that.

>>>>>>>>>> Thank you for this note of accuracy. We have, as suggested, motivated our statement adding the following part to the manuscript: “Online platforms, such as Instagram, allow free social interactions and conversations, and provide a lens through which competing visions on different energy related public issues (Li et al., 2019). Emotions and cognition-related variables have an explanatory power in relation to energy-related decisions (Cousse et al., 2020). Affective reactions to energy technologies influence the way people look for information, their energy technology preferences, and the behavioral responses to energy projects (Sütterlin and Siegrist, 2017). Thus, Instagram can be a driver of the use of renewable energy, having a role not only in perceptions of various technologies but also influencing people's intentions to use renewable energy sources (Zobeidi et al., 2021).”

 

4. "...Sentiment Analysis..." What are the other feasible alternatives? 

>>>>>>>>>> Thank you for your comment. After another literature review, we have added the following alternatives to section 2.2. Word associations in a socio-cognitive approach. In the manuscript: “Social media certainly is an arena for public emotions and cognitions and their analytics can be multiple, including lexical/picture analysis and statistical approaches. For example, text mining derives concepts and themes that carry meaningful meanings for users (Lai and To, 2015). Co-occurrence and frequency analysis, on the other hand, aim to find similarities of meaning between and within word patterns in order to uncover latent structures of mental and social representation (Lancia, 2007). Another example is network analysis, which provides through graphical representations the ability to estimate complex patterns of relationships and the structure can be analyzed to reveal the basic characteristics of a network (Hevey, 2018). The technique we used for the study of emotions and cognitions is Sentiment Analysis, which deals with the detection and classification of sentiments in texts into several classes of emotions and cognitions (Balahur et al., 2018).

 

5. "linguistic associations elicited by wind, solar, geothermal energies..." What are the advantages of adopting this particular metric over others in this case? 

>>>>>>>>>> Thank you for your question. Mental and linguistic representations are important and decisive because they reflect realities and perceptions, which influence the decision for or against a specific energy supply solution and project (Zaunbrecher et al., 2018). Thus, this study gives information such as opinions, attitudes, and feelings expressed in text (whether the semantic orientation in positive, negative or neutral classification words). Further, each technology in a place scale projects should be approached in a different way when trying to manage processes of social acceptance. Communication strategies should thus be targeted based on specific words and the linkage between infrastructures. 

 

6. "The justice word has also a big frequency in the planet cluster," How will this affect the results? More details should be furnished.

>>>>>>>>>> Thank you for your comment. We have furnished more details in the manuscript as follow: “The importance of justice expectations and perceptions is highlighted in the existing acceptance models for RETs (Karakislak et al., 2021). The environmental justice concerns include distributive and procedural claims, as well as recognition and participation factors (Schlosberg, 2007). Environmental justice research has expanded to a more essentially involved field that examines additional layers of the relationship between people and environmental issues (Walker, 2009). However, attachment to the planet may mean altogether different things for British or German, Polish or Lithuanian, and so on (Lewicka, 2011). In this case, we can emphasize that the construct planet is linked to the idea of justice, as well as the climate change and health issues. This result should be studied in future research.”

  

7. "there is no strong relations between the Instagram posts, RETs, and planet" it does not clearly follow out of the literature discussion that you have given.

>>>>>>>>>> Thank you for your comment. We have added the following part to the manuscript in order to be clearer: “These results are in line with the ‘psychological distance’ (Milfont, 2010) which argues that things of value to individuals must be close rather than distant. On the other hand, our results are not in line with other studies which claim that people label themselves as ‘global citizens’, underlining the importance of the interplay between global and national attachments (Devine et al., 2015). Heise (2008) claimed that we need a ‘sense of planet’ as much as a ‘sense of place’. As we have already shown, in our dataset the construct planet evokes more words related to climate change or justice topics, rather than words strictly related to RETs. We encourage future studies in this direction.”

 

8. Moreover, the manuscript could be substantially improved by relying and citing more on recent literatures about real-life case studies on RET such as the followings:

https://doi.org/10.1016/j.seta.2021.101929

https://doi.org/10.1016/j.applthermaleng.2021.116756

>>>>>>>>>> Thank you very much for this suggestion. After reading the interesting studies intensively, we unfortunately did not find a sufficient relation of their technical focus to the psychological focus of our paper. Therefore, we would refrain from citing them. If we have missed something here, we would be grateful for a bit more detail on where exactly the studies would enrich our manuscript.

Reviewer 2 Report

Title: Not all places are equal: Using Instagram to understand 2 cognitions and affect to renewable energy infrastructures

Manuscript ID: sustainability-1605434

In this article, the authors aim to increase the understanding of people-place relations by investigating the relationship between Instagram posts place-level (categorized from local 23 to planet) and sentiments expressed in said posts dependent on different energy infrastructures (solar, wind, biomass, geothermal, powerlines, and renewable energy in general). The authors have presented very good results. I feel this study has innovative and key findings, which may significantly contribute into the scholarly literature.

However, there are few minor issues, which need to be corrected before it reaches to the standard of Sustainability journal.

1. I have tried and cannot find the research gap's identification in this paper. It is not provided in introduction section. Please pay more energy for this.
2. The motivations and contributions are not clearly highlighted in Introduction Section
3. I would like to see the main advantageous of the present article in comparison with the previous works.

 

 

Author Response

Reviewer #2

1. I have tried and cannot find the research gap's identification in this paper. It is not provided in introduction section. Please pay more energy for this.

>>>>>>>>>> Thank you for your comment. We have added some parts to the Introduction to better explain the research gap and our contribution. In the manuscript: “Online platforms, such as Instagram, allow free social interactions and conversations, and provide a lens through which competing visions on different energy related public issues [8]. Emotions and cognition-related variables have an explanatory power in relation to energy-related decisions [13]. Affective reactions to energy technologies influence the way people look for information, their energy technology preferences, and the behavioral responses to energy projects [14]. Thus, Instagram can be a driver of the use of renewable energy, having a role not only in perceptions of various technologies but also influencing people's intentions to use renewable energy sources [15]. However, so far, only a small number of studies has investigated people-place relationships in the context of the energy transition via online content. To address this research gap, this study aims to increase the understanding of people-place bonds by investigating the relationship between Instagram posts place-level and sentiments dependent on different energy infrastructures”.

 

2. The motivations and contributions are not clearly highlighted in Introduction Section

>>>>>>>>>> Thank you for your comment. We have added some parts to the Introduction in order to better explain our motivations and contribution. In the manuscript: “The paper provides insights into individuals’ consideration of RET on Instagram, contributing to a better understanding of the emotions and cognitions related to RET in different place-levels. Furthermore, the paper provides knowledge in which a specific emotion and/or cognition is linked to a specific renewable energy source from local to planet place-level.”

 

3. I would like to see the main advantageous of the present article in comparison with the previous works.

>>>>>>>>>> Thank you for this suggestion. Our research, compared to previous works, increases understanding of how place-level is used to describe RET on Instagram. As we have pointed out in the manuscript, this study is the first to investigate Instagram posts in the context of the energy transition and people-place relationships. Furthermore, we analyzed the cognitive and emotional words linked to the scale of place (from local to global) describing the RETs on Instagram. A good understanding of the public's affective reactions and communication elicited by energy technologies is crucial to anticipate signs of public concern. In order to provide more insight on the advantages of the present paper, we added this part to the manuscript in the paragraph 2.1. People-place relations: “Research in the renewable energy area often focuses on the study of the impact of one renewable energy source (e.g. [33]), or on the relationship between two energy technologies and their support/opposition (e.g. [34]). The following research proposes a combined approach in which place, RETs, powerlines, and their ties are the major factors of the study, considering a systemic picture of the coexistence of the technologies. Thus, the research offers insights useful to practitioners who struggle with knowing how to deal with people’s responses in an adequate way [35]”.

Reviewer 3 Report

The article is the first to investigate Instagram posts in the context of the energy transition and people-place relationships. People from different place scales (from cities to the planet) may have different attitudes and sentiments towards renewable energy infrastructures and they may express their emotions through Instagram. The article collects 1500 Instagram posts, mainly using the methods of LIWC software and multiple linear regressions to analyze Instagram posts data, aiming at showing the relationships among people’s response, place scales and renewable energy infrastructures, which gets good analysis results and arouses wide interest from other researchers. The article could be accepted after the following questions are clearly addressed.

1. There are a few grammatical errors.
2. What criteria were used to select these 1500 posts? In other words, why these 1500 posts were selected?
3. What is the result of the sentiment analysis with LIWC?
4. More Instagram posts should be displayed and explained.
5. The conclusion is not clear and profound enough.
6. Some related references are suggested to be cited, such as 10.3389/fenrg.2020.00167; 10.3389/fenrg.2020.00116.

Author Response

Reviewer #3

1. There are a few grammatical errors.

>>>>>>>>>> Thank you for this comment. A native English speaker has proofread the current version of the manuscript.  

 

2. What criteria were used to select these 1500 posts? In other words, why these 1500 posts were selected?

>>>>>>>>>> Thank you for this question. The 1500 posts (the 250 most recent posts for each hashtag) used in this study were scraped from public Instagram accounts (without privacy restriction) on 17^th September 2020. We chose to sample 250 posts for each hashtag because we expected a small effect size (see for example Boulianne, 2019). We performed manual post scraping which is not feasible over a large number of posts. Instagram restricts the number of posts that can be scraped free and does not allow crawling for specific timeframes. As such, crawling a relatively small number of the most recent posts per hashtag is the next best alternative. Furthermore, the data collection by time series will not be possible considering that the amount of daily-published posts per hashtag is very different. To achieve the same number of posts per hashtag, the dataset was filtered on "recent" not on "most popular" posts at the moment of scraping. 

Furthermore, we have analyzed the length of the posts in order to give more validity to our sample. In detail, the length of the 1500 posts is M = 63.72 and SD = 51.72. The length varies from M = 47.56 for the #powerlines posts to M = 73.26 for the #windenergy posts. In addition, we have made another validation step, scraping the 30% of the posts, for a total of 450 posts. We have evaluated them with regard to their length. In this case, the length of the posts is M = 67.8 and SD = 49.15. 

The hashtags selected were #windenergy, #solarenergy, #geothermalenergy, #biomass, #powerlines, #renewableenergy resulting in 1,500 posts in total. We decided to use these specific RET hashtags (wind, biomass, geothermal) because they have a strong local penetration, becoming subjects with high consideration and discussion by the communities (Ochoa, 2019). Solar was added due to its broad distribution even though it is not conflict related as the others. Powerlines are central for energy infrastructure and often contested, thus included. To gain an overall overview, we integrated the hashtag #renewableenergy. We have described this accordingly also in paragraph 3. Method and procedures and in section 3.1. Data source: scraping data from Instagram posts.

 

3. What is the result of the sentiment analysis with LIWC?

>>>>>>>>>> Thank you for your question. The output of the software is the percentages of total words within a text. The LIWC2015 output was statistically investigated through the Multiple Linear Regression on JASP 0.12.2.0. For the H1.1 (Instagram posts including city and region words are more strongly connected to affective words about RETs than posts with country and planet words), we used the Emotional Processes (Affective Process, Positive and Negative Emotions) LIWC2015 output. For the H1.2 (Instagram posts including country words are more strongly connected to risk words about RETs than posts with city, region, and planet words), we used the Risk LIWC2015 output. For the H1.3 (Instagram posts including planet words are more strongly connected to cognitive words about RETs than posts with city, region, and country words), we used the Cognitive Processes LIWC2015 output (see Table 2).

We conducted a sentiment analysis with all the words from every post. Five multiple linear regressions were calculated to investigate the associations of the word counts of city, region, country, and planet with affect, positive emotion, negative emotion, cognitive process, and risk variables. These five multiple linear regressions were done first on the whole simple (N = 1,500 posts). The analysis of the sample has shown the following results.

One multiple linear regression was calculated to predict affect by city, region, country, and planet word count. The regression model was significant (F (4, 1491) = 4.57, p = .001) and accounted for 1% of the variance of the dependent variable. City (β = -.07, p = .009) and planet (β = -.06, p = .03 were significant predictors of affect. That means, that if cites and planet (1 or several) are mentioned, this is associated with .07 (for city) and 0.6 (for planet) decrease in affect used in captions and hashtags.

A second multiple linear regression was calculated to predict positive emotions by city, region, country, and planet word count. The regression model was significant (F (4, 1491) = 4.98, p < .001) and accounted for 1% of the variance of the dependent variable. City (β = -.05, p = .05), region (β = -.07, p = .006) and planet (β = -.06, p = .03) were significant predictors of positive emotions.

A third multiple linear regression was calculated to predict negative emotions by city, region, country, and planet word count. The regression model was significant (F (4, 1491) = 3.59, p = .006) and accounted for 1% of the variance of the dependent variable. City (β = -.06, p = .03) and region (β = .09, p < .001) were significant predictors of negative emotions.

We have described this accordingly also in paragraph 3.3. Sentiment analysis with LIWC, 3.1. Data source: scraping data from Instagram posts, 4.3 Sentiment Analysis and multiple linear regressions, and 4.4 Exploratory findings.

 

4. More Instagram posts should be displayed and explained.

>>>>>>>>>> Thank you for this comment. In paragraph 3.1. Data source: scraping data from Instagram posts we have explained Instagram in this way: “Instagram provides metadata such as usernames, time and date of creation, caption, comments (user and time information for comments), tags, likes, and location information when users have geotagged their posts”. In order to be clearer, in the same paragraph we have added more information about the Instagram posts: “Figure 2 gives an example of an Instagram post and the information it contains such as a picture, an ID name, a place in the geotag, and a caption (which includes the hashtags).”

 

5. The conclusion is not clear and profound enough.

>>>>>>>>>> Thank you for your comment. We have read the Conclusion again intensively and sharpened it in some parts. For example, we have deeper reflections on the planet-place results in our dataset. In fact, in our sample there are no strong relations between the Instagram posts, RETs, and planet. In the manuscript: “These results are in line with the ‘psychological distance’ (Milfont, 2010) which argues that things of value to individuals must be close rather than distant. On the other hand, our results are not in line with other studies which claim that people label themselves as ‘global citizens’, underlining the importance of the interplay between global and national attachments (Devine et al., 2015). Heise (2008) claimed that we need a ‘sense of planet’ as much as a ‘sense of place’. As we have already shown, in our dataset the construct planet evokes more words related to climate change or justice topics, rather than words strictly related to RETs. We encourage future studies in this direction”.

Furthermore, we added: “Social media users did not use relatively more risk words for any place scale we investigated in this study. This is in line with prior studies where (acceptance of) renewable energy technologies such as biogas were connected to risk perceptions while place attachment was unconnected [52]”.

 

6. Some related references are suggested to be cited, such as 3389/fenrg.2020.00167; 10.3389/fenrg.2020.00116.

>>>>>>>>>> Thank you very much for this suggestion. After reading the interesting studies intensively, we unfortunately did not find a sufficient relation of their technical focus to the psychological focus of our paper. Therefore, we would refrain from citing them. If we have missed something here, we would be grateful for a bit more detail on where exactly the studies would enrich our manuscript.

Reviewer 4 Report

This submitted manuscript seems to be an interesting content. It has comparison examples of the proposed method derived from hypotheses of collected social media. I recommended to be published. However, the following points are preferable to clarify:

1) As some limitations meet in this method, how to maintain the accuracy of the results.

2) It may also be sentiment about the procedure for using renewable energy, how the method can provide the recommendation that the energy needs are real and can be fulfilled, for example.

3) About the many varieties of social media, what is the consideration that through Instagram will provide rational results.

Author Response

Reviewer #4:

1. As some limitations meet in this method, how to maintain the accuracy of the results.

>>>>>>>>>> Thank you for your comment. We have reflected on the accuracy of the results, and we agreed that despite the method has some limitations, we have used aspects of novelty and rigor in order to maintain the accuracy of the research. For example, as suggested from Sovacool et al., (2018) we have brought attention to the importance of clearly articulating research questions, objectives, and designs. Furthermore, we have provided a framework for conceptualizing novelty and pre-registered our hypotheses. The hypotheses have been pre-registered on https://aspredicted.org/create.php and made public on September 14th, 2020. Moreover, in order to have validity and accuracy of our sample, two coders categorized the Instagram posts. In fact, we coded the posts regarding four place categories (city, region, country, and planet) based on the available information in hashtags, place geotagging, and caption. One author categorized all the posts (1500) into the categories. A second author coded 20% of the posts, for a total of 300 posts, independently from the first author. Inter-rater reliability achieved satisfactory significance (85,7%) between the two coders. If an association was not categorized to the same category by both authors, a discussion ensued to find a common and adequate solution. We repeated this procedure until all places were assigned to one category by common accord. Moreover, in order to provide more information about the corpus of the text, we have added the mean of the post lengths. In addition, we have made another validation step, scraping the 30% of the posts, for a total of 450 posts. We have evaluated them with regard to their length. We can conclude that, being the mean of the length posts approximately the same, this is evidence of the good sample we are using. In the whole manuscript, we have made suggestions for future researchers in order to improve the research design, especially using other complementary methods for covering limitations.

 

2. It may also be sentiment about the procedure for using renewable energy, how the method can provide the recommendation that the energy needs are real and can be fulfilled, for example.

>>>>>>>>>> Thank you for this comment. The interrelations between emotions and language have achieved a significant scope and diversification (Kecskes, 2010). It has been shown that there is a fundamental relationship between the structures of mental life and the production of written and/or verbal discourse (Schacter and Addis, 2007). The terms people use in their daily lives can provide important information about their beliefs, attitudes, and social relationships. Mental representations are important and decisive because they reflect realities and perceptions, which influence the decision for or against a specific energy supply solution and project (Zaunbrecher et al., 2018). Social media gives everyday communication as their subject and offers the manifestation, interpretation, and processing of emotions in interaction using natural conversations. Social media not only strengthens social ties and interactions among communities, but also cultivates massive public opinions through emotional and cognitive words (Li er al., 2019). A high number of researchers on energy transitions have used different social media platforms as data sources (e.g., Nuortimo and Härkönen, 2018). Social media provides an opportunity to examine the dynamics of social perception of energy issues (such as emerging technologies, energy conservation, and environmental impacts). The way in which information about renewable energy is shaped influences the people's perception and evaluation of RETs (Devine-Wright, 2008). Thus, this study using a social media platform, gives an overview of the description of different energy technologies. Emotions and cognition-related variables at different place-scales have an explanatory power in relation to energy-related decisions (Cousse et al., 2020). Affective reactions to energy technologies influence the way people look for information, their energy technology preferences, and the behavioral responses to energy projects (Sütterlin and Siegrist, 2017).

 

3. About the many varieties of social media, what is the consideration that through Instagram will provide rational results.

>>>>>>>>>> Thank you for your question. Each social media satisfies different needs in users (Zhu & Chen, 2015) and each platform can be a good resource for research purposes. From a researcher point of view, it is important to know the main perspective of the social media network and what software and tools to use to scrape and analyze data. Each social platform has key points that should be recognized. Then, based on the research questions and the theoretical model, decide which social media platform fits the research objectives. For example, Facebook aims to “build technologies that help people connect with friends and family, communities, and grow businesses” (Statista, 2022). Twitter is a social media platform about “what people are talking about right now” and aims “to serve the public conversation” (Statista, 2022). Instagram’s purpose is to bring “you closer to the people and things you love” and to “connect with more people, build influence, and create compelling content that’s distinctly yours” (Statista, 2022). According to (Zhu & Chen, 2015)’s framework, Instagram can be viewed as a creative outlet social media platform where hobbies and interests can be shared in a visual-focused environment. In the paper we have pointed out the reason for using Instagram instead of other media platforms. From the manuscript: “The advantages of using Instagram for this research are: i) the number of words used in the caption is unlimited, contrary to other platform (e.g. Twitter) and this is an important advance for the purpose of this research based on text analysis. ii) Instagram is known for the strong use of hashtags, both as a description of a picture/video and as a search term for particular topics (Handayani, 2015). The extensive use of hashtags allows us to study the set of words associated with RET descriptions; iii) Instagram as a web source has never been used for the studying of RETs. Aware of the fact that Instagram is social media for sharing videos and pictures as well as text, we want to clarify that the analyses of this paper are focused on the analytical procedure of the text and not on the analyses of the images”. A good understanding of the public's affective reactions and communication elicited by energy technologies is crucial to anticipate signs of public concern. The developer, for example, can communicate directly with consumers through blogs, online content, and videos with the keyword language used by consumers. Concluding, Instagram can be a driver of the use of renewable energy, having a role not only in perceptions of various technologies but also influencing people's intentions to use renewable energy sources (Zobeidi et al., 2021). Instagram has a growing role in shaping public opinion and is a virtual place where people share their beliefs and emotions with others. For these reasons, rather than rational results, we evaluated how people express their opinions, as well as ideas of the energy transition topic by following specific renewable energy technology hashtags. 

Round 2

Reviewer 1 Report

The author did not answer all of my questions accordingly.
They just have responded to some parts of issues and have left some others!
I give one more chance to authors to answer ALL of my questions/ comments.
If they cannot address all of my questions/ comments, I have no choice just to reject the paper

Author Response

The author did not answer all of my questions accordingly. They just have responded to some parts of issues and have left some others! I give one more chance to authors to answer ALL of my questions/ comments. If they cannot address all of my questions/ comments, I have no choice just to reject the paper

>>>>>>>>>> Thank you for your comment. We have carefully re-read our responses. We have added more information to the questions trying to be as clear as possible. If we are still missing some important part, we would be grateful for a bit more detail on where exactly the questions are not sufficiently answered. The replies to the comments are provided below.

 

• "In recent years, social media has become integrated into many aspects o..." This is strong and contentious statement without proof?

>>>>>>>>>> Thank you for this comment. The statement "In recent years, social media has become integrated into many aspects of our daily language use through sharing and interaction with online content and connecting with other people. Social media has experienced tremendous growth in its user base and has influence public discourse and communication in society" is written in the Introduction section. After a careful review, we have added this reference to the statement: Li, R., Crowe, J., Leifer, D., Zou, L., & Schoof, J. Beyond big data: Social media challenges and opportunities for understanding social perception of energy. Energy Research & Social Science 2019;56(101217). In the cited paper, the authors explain and demonstrate the importance of social media not only in people's everyday lives, but also as data collection and analysis tools. For this reason, we think the paper is appropriate and it is an interesting reference for the readers.

 

• ”RETs on Instagram posts?,,," If this is your own conclusion, it is out of place here in same paragraph with statement?

>>>>>>>>>> While we are not sure we understand the comment correctly, we would like to clarify that this is one of our research questions (which places do people associate with RETs on Instagram posts?), which we derived from the assumptions we discussed in the paper. This question also arises because, despite the importance that social media has for modern discourse; to the authors’ knowledge, no study has yet investigated place-relationships in the context of RETs on social media platforms. We seek to fill this research gap by examining the potential relationship between sentiments articulated in Instagram content related to RETs and places. Again, we do not really understand what the comment means. If we are still missing some important parts, we would be grateful for more details.

 

• "...studying public perception of energy technologies" you should motivate why you say that.

>>>>>>>>>> Thank you for this note of accuracy. You are referring to this statement “The study of people-place relations on Instagram provides insights in considering both affective and cognitive factors studying public perception of energy technologies”. We have, as suggested, motivated our statement adding the following part to the manuscript in the Introduction section: “Online platforms, such as Instagram, allow free social interactions and conversations, and provide a lens through which competing visions on different energy related public issues (Li et al., 2019). Emotions and cognition-related variables have an explanatory power in relation to energy-related decisions (Cousse et al., 2020). Affective reactions to energy technologies influence the way people look for information, their energy technology preferences, and the behavioral responses to energy projects (Sütterlin and Siegrist, 2017). Thus, Instagram can be a driver of the use of renewable energy, having a role not only in perceptions of various technologies but also influencing people's intentions to use renewable energy sources (Zobeidi et al., 2021). However, so far, only a small number of studies has investigated people-place relationships in the context of the energy transition via online content. To address this research gap, this study aims to increase the understanding of people-place bonds by investigating the relationship between Instagram posts place-level and sentiments dependent on different energy infrastructures”.

 

• "...Sentiment Analysis..." What are the other feasible alternatives?

>>>>>>>>>> Thank you for your comment. After another literature review, we have added the following alternatives to section 2.2. Word associations in a socio-cognitive approach: “Social media certainly is an arena for public emotions and cognitions and their analytics can be multiple, including lexical/picture analysis and statistical approaches. For example, text mining derives concepts and themes that carry meaningful meanings for users (Lai and To, 2015). Co-occurrence and frequency analysis, on the other hand, aim to find similarities of meaning between and within word patterns in order to uncover latent structures of mental and social representation (Lancia, 2007). Another example is network analysis, which provides through graphical representations the ability to estimate complex patterns of relationships and the structure can be analyzed to reveal the basic characteristics of a network (Hevey, 2018). The technique we used for the study of emotions and cognitions is Sentiment Analysis, which deals with the detection and classification of sentiments in texts into several classes of emotions and cognitions (Balahur et al., 2018)”. As we have explained, for the study of social media platforms there are several techniques that can be used. In our paper, we wanted to focus on the mental associations between RETs and places mentioned in Instagram posts. Our interest was also to study the valence of the words used to describe the posts, if they were more emotional or cognitive. For all these reasons, we decided to use the sentiment analysis because it is more suitable for the purpose of research.  

• "linguistic associations elicited by wind, solar, geothermal energies..." What are the advantages of adopting this particular metric over others in this case?

>>>>>>>>>> Thank you for your question. Researchers traditionally collect social perception and opinions on energy development and utilization through quantitative structured surveys, qualitative semi-structured interviews, direct observation and panel participation (e.g., Clarke et al., 2016). Studying with social media platforms not only strengthens social ties and interactions among communities, but also cultivates public opinions on socio-economic, scientific, and political issues. On the study of social media content, the mental and linguistic representations are important and decisive because they reflect realities and perceptions, which influence the decision for or against a specific energy supply solution and project (Zaunbrecher et al., 2018). Thus, this study gives information such as opinions, attitudes, and feelings expressed in text (whether the semantic orientation in positive, negative or neutral classification words). Further, each technology in a place scale projects should be approached in a different way when trying to manage processes of social acceptance. Communication strategies should thus be targeted based on specific words and the linkage between infrastructures.

 

• "The justice word has also a big frequency in the planet cluster," How will this affect the results? More details should be furnished.

>>>>>>>>>> Thank you for your comment. We think that the justice construct in the planet cluster has an important relevance. Interestingly, in our dataset the planet construct evokes more words related to climate change or justice issues, rather than words closely related to RETs. For this reason, we explained the importance of this justice-planet association in the manuscript in section 4.2 Cluster analysis in Instagram posts as follow: “The importance of justice expectations and perceptions is highlighted in the existing acceptance models for RETs (Karakislak et al., 2021). The environmental justice concerns include distributive and procedural claims, as well as recognition and participation factors (Schlosberg, 2007). Environmental justice research has expanded to a more essentially involved field that examines additional layers of the relationship between people and environmental issues (Walker, 2009). However, attachment to the planet may mean altogether different things for British or German, Polish or Lithuanian, and so on (Lewicka, 2011). In this case, we can emphasize that the construct planet is linked to the idea of justice, as well as the climate change and health issues. This result should be studied in future research.”

 

• "there is no strong relations between the Instagram posts, RETs, and planet" it does not clearly follow out of the literature discussion that you have given.

>>>>>>>>>> Thank you for your comment. We have added the following part to the manuscript in order to be clearer: “These results are in line with the ‘psychological distance’ (Milfont, 2010) which argues that things of value to individuals must be close rather than distant. On the other hand, our results are not in line with other studies which claim that people label themselves as ‘global citizens’, underlining the importance of the interplay between global and national attachments (Devine et al., 2015). Heise (2008) claimed that we need a ‘sense of planet’ as much as a ‘sense of place’. As we have already shown, in our dataset the construct planet evokes more words related to climate change or justice topics, rather than words strictly related to RETs. We encourage future studies in this direction.” As we have explained, our results are in line with a portion of the literature and not in line with other studies. Our results underlined that the mental association between planet, RETs, and place is a particularly relevant construct. Therefore, in the paper, we emphasized that we do not currently have a clear answer to this question, but various referenced theories cited help to understand in part our results (and leaves open the space for new considerations and future studies).

• Moreover, the manuscript could be substantially improved by relying and citing more on recent literatures about real-life case studies on RET such as the followings:

https://doi.org/10.1016/j.seta.2021.101929

https://doi.org/10.1016/j.applthermaleng.2021.116756

>>>>>>>>>> Thank you very much for this suggestion. After reading the interesting studies intensively, we unfortunately did not find a sufficient relation of their technical focus to the psychological focus of our paper. Therefore, we would refrain from citing them. If we have missed something here, we would be grateful for a bit more detail on where exactly the studies would enrich our manuscript.

Round 3

Reviewer 1 Report

Accept!