## 3 Methodology
### SEBD Architecture and Framework Phases
The estimated number of accounts for each hashtag or keyword was \((100_{accounts}+100_{accounts}\times 10_{followers}+100_{accounts}\times 10_{following})\), except for the first three hashtags in Table 2, for which the estimated number was \((35_{accounts}+35_{accounts}\times 10_{followers}+35_{accounts}\times 10_{following})\). These three hashtags/keywords were collected one after another; therefore, we decreased the number of accounts. ### Selected Features

For each user, follower, and followed account, we extracted only the profile features. These profile features proved to be optimal in identifying social bot account [17; 27; 47]. Thus, the goal of using fewer profile features, in addition to their performance, was to minimize the requirements for preprocessing and encoding, in order to speed up the learning process. This would reduce the memory space requirements and computational costs of stream prediction. Therefore, we selected 6 numerical features and 4 categorical features. Numerical features: These profile features have numerical values. They are described below:

* Follower count: the number of users who are following this user account. * Favorite count: the number of tweets a user has liked since the account creation date. * Status count: the total number of tweets and retweets issued by the user. * Friend count: the total number of accounts this user is following. * Age in days: the total number of days since the account was created as of the date of retrieving the data. * Screen name length: the total number of characters (digits) in the screen name. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Hashtag** & **Domain** & **Total Number** & **Trending** & **Combined** & **Worldwide** \\ \hline \#AEWDynamic & Sport & & ✓ & ✓ & ✗ \\ \#AbbottElementary & Sport & 2355 & ✓ & ✓ & ✗ \\ \#Mozz & Sport & & ✓ & ✓ & ✗ \\ \hline \#Cowboys & Sport & 2035 & ✓ & ✗ & ✓ \\ \hline \#PMQs & Political & & ✓ & ✓ & ✗ \\ \#Oscars2023 & Entertainment & 3070 & ✓ & ✓ & ✓ \\ \hline \#ClimateCrisis & - & 1540 & ✗ & ✗ & ✗ \\ \hline \#iOS16 & Technology & 1986 & ✗ & ✗ & ✗ \\ \hline \#ChatGPT & Technology & 1681 & ✓ & ✗ & ✓ \\ \hline \#TheLastofUs & Entertainment & 1972 & ✓ & ✓ & ✓ \\ \hline
**Total** & & **14,639** & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Group 2 hashtags. \begin{table}
\begin{tabular}{c c} \hline \hline
**Hashtag** & **Domain** \\ \hline \#WorldCup2022 & Sport \\ \#Russia OR Ukraine & Political \\ \#Bitcoin & Financial \\ \#GUS16 & Technology \\ \#NotMyKing & Political \\ \#gamescom2022 & Entertainment \\ \hline
**Total** & **4705** \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Group 1 hashtags. Categorical features: These profile features have Boolean values. They are described below:

* Verified: Indicates that the user has a verified account. * Default profile: A true value means that the user has not altered the theme or background of their profile. * Default profile image: A true value means that the user has not uploaded a profile image and the default image is used. * Geo enabled: A true value denotes that the current user attaches geographical data when tweeting or retweeting. Before using these features, the numerical features were normalized to eliminate bias. For the categorical features, true values were converted to 1 and false values to 0. ### Hashtag Selection Criteria

There are many factors that can impact a trending hashtag or keywords. For example, the domain of interest (political or sports) is one of the factors of a trending hashtag. Spatial information on the event of a trending hashtag was noted, as some trends remain trending for hours and end up in the worldwide trending list. Therefore, to evaluate how our model adapted to different hashtags based on location or trending status and domain, we used the following hashtag criteria to collect different hashtags:

* Not trending and trending. * Trending in a specific location vs. worldwide. * In a specific domain vs. multiple domains at once.