Engagement is the foundation of any society. Without it, society crumbles. Strong engagement, on the other hand, allows society to grow beyond its initial boards. It allows every member to benefit from positive growth. When a society begins to stagnate or decline, engagement is the thing that can restore it to greatness.
Lifeblood of Leo Finance
Engagement is the lifeblood of Leo Finance. Its leadership takes into account user and community input and data from outside the community to determine the best path forward for the group.
Users contribute towards the Leo community's value by investing in the platform, creating and curating posts, and providing critiques and recommendations to the community. Arguably, no one part of the community supersedes the other. Leo can only grow if everyone participates smartly.
I know Leo does well, but how well? Does Leo perform outside of a standard? Is Leo Finance at the top of Engagement metrics? Metrics on community performance are available, but I would like to expand that view to performance predictions ultimately.
Performance Indicators
Indicator Basics
How do we measure a thing? In terms of engagement, I've been taught in the community that the following questions are important performance indicators:
- How many people vote on a post?
- How many people comment on a post?
- Where does #LeoFinance stand in this analysis?
As a side note, I've always wondered which months, days of the week, and times of the day had the highest engagement. My goal was to analyze the following items, over the course of 2020, via Hive SQL:
- Number of votes for posts by community
- Number of post responses by community
Method of Analysis
Thanks to the HiveSQL databases, anyone in the community can help data mine the Hive database. In an article entitled, "HiveSQL is ready with all the Hive blockchain data", @arcange discusses the process to gain access to the Hive databases.
I utilized Microsoft Access & Excel 365 for querying the databases and shaping the data into the charts we'll discuss shortly. I have also narrowed my search to meet the following criteria:
- Only Hive communities starting with "HIVE-" are included in the search due to technical limitations at this time.
- Posts created between 1/1/2020 and 12/31/2020 are considered for this analysis
Overall, 2189 communities were included in the analysis for this post.
2020 Hive Community Trending Results
Top 10 Total Postings by HIVE Group
The graph above represents total postings during the course of 2020 for HIVE communities. Out of 2189 communities, Leo Finance is in the top five.
Top 10 Total Votes by HIVE Group
The graph above represents total votes during the course of 2020 for HIVE communities. Out of 2189 communities, Leo Finance is in the top two.
Top 10 Total Comment Postings by HIVE Group
The graph above represents total comment postings during the course of 2020 for HIVE communities. Out of 2189 communities, Leo Finance is also in the top two.
In Closing
Image by Gerd Altmann from Pixabay
Thank you for joining me on my first journey datamining HIVE.
It seems that Leo Finance is in the top 5 of HIVE communities in posts, votes, and posting comments. I see community members speaking nothing but good about this platform. It's quite impressive to see that their comments about Leo Finance are true.
Also, I'm just amazed at the level of interaction within the HIVE community. There is so much interaction here that I initially questioned the very numbers I saw in the data stream.
Moving forward, I will be able to produce the data and graphs automatically. Also, I would like to include the following metrics in subsequent postings:
- Engagement and curation by date-time
- Expanding the analysis to all communities though I'll have to focus on the "HIVE-" groups for now.
Posted Using LeoFinance Beta
The fact leo is doing great is also the accounts using g it so frequently. But yes all
Is true ! Tags within leo use would be a great one to research aswell and the accounts using leo the most is worth a leo badge hahahah so many ideas 😉
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You're definitely correct about everything.
The problem was my familiarity with the data tables, oh, and time. We've got some heavy hitters already data mining the blockchain and providing great information. I feel like I'm learning from the best here, and I need to take in as much learning as possible from these guys. So, consider me the turtle for now.
One thing that isn't reported regularly is the date-time-rate of engagement. Where is the biggest bang for your buck concerning posting, voting, or commenting? Can I calculate this continuously? I look forward to investigating this info.
Tags, as you mentioned, is also another great metric to review. Thanks for bringing it up!
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The numbers guy here is @abh12345 he will know where to find it and if he doesn’t know it’s not important
Actually, it's because of his posts that I'm taking this direction, but I'm not a fan of data duplication. I can glance over what he covers, but only if I find it's supplemental. So, for now, I'm covering the high overview until I become more familiar with the tables.
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It’s always great to further look into all that’s happening on the platform
I look forward to seeing your efforts in this area :)
Perhaps looking at the largest manual curators (ocdb, curangel, leo.voter, etc) and looking at their vote timings (when are the curators awake?).
The kicker is that they are looking for content, so I feel post timing is not so important as it perhaps was in the past (when some people were waiting for certain accounts to wake up each day).
Thanks for the reply @abh12345! The "biggest bang" I refer to isn't earnings but, instead, for availability. There's a correlation between the timing of the post and earnings, but that's more of a distraction for me right now. Engagement is the key. It's the key to everything.
Whoever made these data tables is truly skilled.
I could almost overlay some of these trends with what I see at work monitoring workgroup trends. I'm still going through those darn candlestick patterns too. Too much to do!
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Ah right, silly me :)
That would involve grouping comment count (depth>0) by day of week, or maybe hour of day perhaps?
Yeah exactly. I have to do groupings like this at work. It can be done, but the beginning part of the build is tediously long due to testing.
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Good to see others delving into the @hivesql DB. I hope you continue to learn and surface some gems :)
Thanks. I look forward to it. I can't help but wonder why everyone isn't doing it. And then I look at those data tables and realize that people don't find it so exciting, lol. I guess we're weird that way.
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Thanks a lot for this brief analysis.
Sorry to be blunt but .. I see your metric more as quantitive than qualitative.
Ps: would you be so kind and open-source your queries? Perhaps in a form of a tutorial :)
Reblogged!
!invest_vote
It is more quantitative. I did a raw data download by quarter and then grouped them into a combined table via Excel to preclude the possibility of duplicate data.
I’d love to open source the workbook. I don’t know how. Is there a place I can upload my work?
Hm, a good question. I really don't know about files like excel or access database. It's easy for text-based files ...
I'll come back if / when I find something suitable.
Good work!
Yes thank you as well. I believe in open source information. I bet my career on it daily at work and welcome any critiques. I’ll also investigate this area. There are some people I can ask.
Also. I wanted to keep things simple at this turn so I can work out any kinks. It’s for this reason I only included an overview
@ervin-lemark denkt du hast ein Vote durch @investinthefutur verdient!
@ervin-lemark thinks you have earned a vote of @investinthefutur !
I love number crunching! Thank you for sharing.
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I love number crunching. I also hate doing it because of how long the initial testing can take before automation. I feel like I’m telling you that I love it, but am too lazy to love doing it lol