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title: 'Mini Project 4 - Who :face_with_monocle:'

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# Mini Project 4 - Who :face_with_monocle: 

## By Group 12 :face_with_cowboy_hat:  (Group 4000: Født I Går (Born Yesterday))

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## Research question :question:
“How are climate positive discourses empowered or challenged by different hashtag communities and ad hoc publics, and how can this be represented through network visualizations” 

## Meta reflections/Introduction: :globe_with_meridians: 
We have yet to make any queries on the TCAT servers, and thus our mini project 4 is used as a reflective assignment in which we wish to work out how we are going to go about our final group project. What we have focused on in this mini project is the creation of a research question which can be used to frame different cases. In this project we have chosen to focus on hashtag communities related or aligned with climate positive discourses, but we would argue that the same question could be used in order to research other subjects, in which conflicting groups and standpoints towards a topic are evident. In order to shed light on cases of empowerment through hashtags communities, we are to render central actors in a certain case visible, but furthermore we have to define what empowerment, and thus “power”, means in the context of our research, in order to understand the research context as a whole. In order to try out this framework on a specific case, we have chosen to research communities aligned with climate positive discourses.

## Research theory and methodology: :brain: 
In this mini-project, we are using network visualisation as a digital method. Thus, we are using visualizations for the purpose of social research (Marres, 2012), which in this case will be focused on the empowerment of the climate change action cause through the use of hashtags. The choice of network visualisations in this mini-project is based on its ability to show connections of actors in a network, which in our research is considered to be highly relevant in order to show how and which actors or groups are supporting the cause. Throughout the project, we are using the framework and vocabulary from visual network analysis: The example of the rio+20 online debate (Venturini et al., 2015), which is specifically focusing on visual analysis of networks. However, as mentioned by venturini et al., it is important to note, that: 

> “The main disadvantage of visual analysis is that it is impossible without some previous knowledge of the data and the phenomenon that they refer to” (Venturini et al., 2015)  

Due to the limitations of a mini-project, we are not capable of gathering the knowledge necessary to grasp this case as a whole. However, we are focusing on how the use of network visualisations can be applied in order to create a general overview of the case of interest. 

As stated in our research question, we are focusing on how the cause of climate change action is empowered and challenged by other actors or groups, connected through the use of specific hashtags. Bruns & Burgess (2011) describes in the text The use of twitter hashtags in the formation of ad hoc publics, how the natively digital object (Marres, 2012), the hashtag, can create hashtag communities. The term covers the ways in which tweets on common topics are bundled together, and how the senders of these tweets are engaging with each other. Thus, it can be argued that these users are creating a community, revolving around the hashtag used, as they mutually start engaging with each other. In our research, this understanding of hashtag based communities becomes immensely useful in the analysis of a hashtag-based network visualisation, as it creates an underlying understanding of which groups that take part in empowering certain hashtags, and thus, which hashtags communities that support the cause of climate change actions. 

The understanding of the term power, and thus empowerment, applied in this mini-project is revolving around the translation model described in The power of association (Latour, 1984). In the text, Latour argues that the significance, or power, of any given “thing”, be it a discourse, political movement, position in government, is upheld, modified or dropped by the people in relation to it. Meaning, the significance of any given phenomena is dependent on people aligning with and supporting it. Thus, the significance of any phenomenon cannot uphold its status of power regardless of its relation to people, it is solely dependent on people continuously carrying and supporting it. By applying this understanding of power to our visualisation, power thus becomes a product of support and association, which in a network visualisation can be seen as the size of each node. The bigger the node, the more associations it has to other hashtags and, thus, the more it is used and supported by different hashtag communities. This makes us able to view which hashtag communities are related to, and by way of rhetoric and words’ sentiment, locate supportive and empowering communities for the cause of climate change.


## Research tools :computer: :hammer_and_wrench: 
To analyze and visualize the empowering hashtags communities, we needed a way to showcase hashtags in relation to our queried hashtags, correlative to the ones used on the TCAT server. In order to do so, we created a Twitter developer account in order to gain access to the Twitter API. To collect our data, we queried keywords “climatecontrol”, “climateaction” and “climatechange” in the Gephi Plugin Twitter Streamer Importer, which collects all associated tweets to the hashtags posted 1 hour from the collection beginning, and then continues until a sufficient amount has been collected. In order to visualize our tweets, we used Gephi to visualize the connection between hashtags, the relevance (times connected) of hashtags and their interrelations to other hashtags used with the queried hashtags. 

## Results :crescent_moon: 

### Gephi Render

![](https://i.imgur.com/qoRBWWj.png)

### Gephi Render - with highlighted clusters

![](https://i.imgur.com/nBuhe7F.jpg)

In our Gephi Render, we have identified the following clusters of hashtag communities of significance in relation to climate change:

- light blue (dark blue outline) :large_blue_diamond:: This cluster has an obvious connection  obvious connection to the hashtag the hashtag #nature, which is related to our queried key words. The cluster consists of different sub-clusters, sharing the interest of nature, such as a #tesla community, a #haikuoftheday community and a #animals community. 
- light blue (light blue outline) :large_blue_circle:: This cluster is similarly interested in nature, but with more emphasis on wildlife preservation, which is also a case closely related to climate change. The Cluster is mainly geographically attached to #australia and #newsouthwales (in Australia).
- pink :pisces:: This cluster is interested in the urban perspective of climate change, and, furthermore, problems in urban enviornments emphasizing change through #urbandecay, #humanity and #dystopia, for example.
- purple :purple_heart:: In this cluster the center of the cluster is #climateaction, and it is interesting to see that country names as Candada, Italy, Spain and USA are included in this cluster, representing geographically specific hashtag communities related to the climate action cause. The cluster is interested in other climate chance hashtags as #globalwarming, #airpollution and #fossilfuels and furthermore the cluster is interested in contemporary political interested with hashtags as #biden2020 and #biden.
- green :green_heart::The green cluster is interested in the financial sector with hashtags as #bankofengland, #assetsmanagement and #financialservices. After a little research, we can see that #bankofengland has launched initiatives to better climate through climate testing of the UK financial  sector.
- gray (bridging cluster) :gear:: The grey cluster bridging #uk and #enviornment with #climateaction is a scientific orientated cluster with hashtags such as #climatology, #climatescience and #carbondioxide.
 

## Conclusion :boom: 
In this study, we have attempted to show how a framework can be applied on a case where we wish to study the relation between groups and individuals by way of queried hashtags with a pro climate change discourse and related hashtag communities.

We acknowledge the fact that we cannot present in-depht conclusions and explanations of our observations because we lack the underlying knowledge of the related hashtag communities present in the network vizualisation, as well as substantiating sources related to the subject of study.

However, our mini-project gives a clear understanding of the advantages of the visualization tools. With a thorough examination of the hashtags and their background, we assess that this analysis could be central to understand the empowerment of causes through hashtags and hashtag communities.


## References :linked_paperclips: 
- Bruns, A., & Burgess, J. (2011). The use of Twitter hashtags in the formation of ad hoc publics. I A. Bruns & P. De Wilde (Red.), Proceedings of the 6th European Consortium for Political Research (ECPR) General Conference 2011 (s. 1–9). The European Consortium for Political Research (ECPR). https://eprints.qut.edu.au/46515/
- Latour, B. (1984). The Powers of Association. The Sociological Review, 32(1_suppl), 264–280. https://doi.org/10.1111/j.1467-954X.1984.tb00115.x
- Marres, N. (2012). The Redistribution of Methods: On Intervention in Digital Social Research, Broadly Conceived. The Sociological Review, 60(1_suppl), 139–165. https://doi.org/10.1111/j.1467-954X.2012.02121.x
- Venturini, T., Jacomy, M., & Pereira, D. (2015). Visual Network Analysis.



