## 4 Results of the Software-Prototyping
### From Logging to Structured Logging
#### 5.3.2 Long-Term Evaluation Phase of Use Case 4

A long-term recording was then done as a second long-term evaluation phase and was used to track and record the most frequent used stock symbols identified in the screening phase. This evaluation phase lasted from February 2022 until the middle of August 2022. In this evaluation phase, just one infrastructure downtime occurred due to a shutdown of electricity of the author's institute. However, this downtime was not due to or related to the presented unified logging stack (see Figure 8). #### 5.3.3 The Instrumentation Approach Applied in Both Phases

The recording was done using the following source code, see Listing 5, compiled into a Docker container, that has been executed on a Kubernetes cluster that has been logged in **Use Cases 1, 2, and 3**. FileBeat was used as a log forwarding component to a background ElasticSearch database. The resulting event log has been analyzed and visualized using Kibana. Kibana was used as well to collect the data in form of CSV-Files for the screening and the evaluation phase. Figures 7, 9 and 10 have been compiled from that data. This setting followed the unified and simplified logging architecture presented in Figure 4 exactly. kind=''reply''ifstatus._json[''in_reply_to_status_id'']elsekindkind=''retweet''if'retweeted_status'instatus._jsonelsekindkindkind=''quote''if'quoted_status'instatus._jsonelsekindevent.update(lang=status.lang,kind=kind,message=status.text)
* }
* with event.child('user')asusr:name=status.user.nameifstatus.user.nameelse''unknown'usr.update(lang=status.lang,id=status.user.id_str,name=name,screen_name=f''e(status.user.screen_name)'',message=status.text,kind=kind)
* }
* for taginstatus.entities['hashtags']:withevent.child('hashtag')ashashtag:hashtag.update(lang=status.lang,tag=f''#{tag['text'].lower())'',message=status.text,kind=kind)
* }
* forysminsatus.entities['mymbola']:withevent.child('symbol')assymbol:symbol.update(lang=status.lang,symbol=f''${sym['text'].upper())'',message=status.text,kind=kind)
* symbol.update(screen_name=f''@{status.user.screen_name}'')')
* foruser_mentioninstatus.entities['user_mentions']:withevent.child('mention')asmention:.update(lang=status.lang,screen_name=f''@{user_mention['screen_name']}'',message=status.text,kind=kind)
* }
* record=Twista(KEY,SECRET,TOKEN,TOKEN_SECRET)ifLANGUAGES:record.filter(track=TRACK,languages=LANGUAGES)else:record.filter(track=TRACK)

#### 5.3.4 Observed and Recorded Twitter Behaviour in Both Phases of Use Case 4

According to Figures 7 and 8, just every 100 th observed event in the screening phase was a stock symbol. That is simply the \"ground-truth\" on Twitter. If one is observing the public Twitter stream without any filter, that is what you get. Thus, the second evaluation phase recorded a very specific \"filter bubble\" of the Twitter stream. The reader should be aware that the data presented in the following is a clear bias and not a representative Twitter event stream; it is clearly a stock market focused subset or, to be even more precise, a cryptocurrency focused subset, because almost all stock symbols on Twitter are related to cryptocurrencies. It is possible to visualize the resulting effects using the recorded data. Figure 9 shows the difference in language distributions of the screening phase (unfiltered ground-truth) and the evaluation phase (activated symbol filter). However, in the screening phase, English (en), Spanish (es), Portugese (pt), and Turkish (tr) are responsible for more than 3/4 of all traffic; in the evaluation phase, almost all recorded Tweets are in English. Thus, on Twitter, the most stock symbol related language is clearly English. Although the cryptocurrency logging was used mainly as a use case for technical evaluation purposes of the logging library prototype, some interesting insights could be gained. For example, although Bitcoin (BTC) is likely the most prominent cryptocurrency, it is by far not the most frequently used stock symbol on Twitter.