## 3 Methodology
### Stage 2: Choosing the Right Datasets  
We utilized the emotions dataset provided in [19] for studying DSSMs. This dataset consists of labeled comments extracted from the Jira platform. Jira is an issue-tracking system (ITS) that is used for software task tracking, ticketing systems, and project management [20]. It is commonly used in Agile development with methodologies such as Scrum or Kanban board.  
To investigate DISMs, we expanded our scope beyond Jira and included the Twitter dataset detailed in [21]. Twitter, currently named \"X\", is a microblogging platform that allows users to communicate by short messages of up to 280 characters [22]. The platform facilitates one-way communication, where the users post content while their followers can engage with the content through comments [23].  
We opted to use a Reddit dataset [24] as a middle-ground option to explore both DSSMs and DISMs. Reddit is an online discussion forum where users can create communities, called subreddits, to discuss specific topics [25]. Each subreddit has its unique culture and moderation policies, making them different from one another.  
Reddit and Twitter have different features that make them unique. On Reddit, users can follow specific subjects through subreddits, while on Twitter, users primarily follow influencers [26]. On the other hand, Jira is a platform that is used for managing and creating software products, and it hosts developer communities [27]. The level of communication on these platforms also differs. Jira involves technical terminology, in which sprints and Agile methodologies contribute to a specialized language that aids precise communication within development teams. Twitter, with its character limit and fast-paced nature, demands quick and impactful messages, which often leads to a preference for direct, casual, and informal communication styles. Meanwhile, Reddit fosters in-depth discussions through longer-form posts and comments that may vary depending on the specific subreddit community [28]. Some discussions can point towards casual or humorous content, while others maintain a more formal and professional atmosphere.  
The Venn diagram shown in Figure 1 displays the semantic distribution of short messages across these platforms. It highlights four intersection regions marked with Roman numerals:  
* The semantic intersection of Twitter and Jira datasets can create a blend of professional and casual communication which can uncover trends and correlations among technical events. It is important to note that a negative sentiment on Twitter may express sadness or anger, whereas, on Jira, it can add valuable feedback and criticism.
* Jira and Reddit dataset messages can span various domains, resulting in a mix of domain-specific vocabulary. It may also induce multi-domain topics, with more complex terminology. For instance, the software development jargon could be mixed with marketing or sales-related vocabulary.
* While Reddit and Twitter datasets tend to cater to different user dynamics and discussion formats, some areas overlap in vocabulary. The language might be informal and focused on news, entertainment, humor, travel, and food, but it may also reveal more in-depth terminology for different topics.
* The semantic intersection of the three datasets may showcase how the technical jargon of Jira joins with social discussions of Twitter and in-depth debates of Reddit.  
Examining the intersection zone might reveal a better understanding of SE sentiments in terms of transparency, optimism, seriousness, sarcasm, criticism, etc.