The proposed analysis aims at providing the first outline of the italian community gathered under the #ita tag within the posting activity of the year 2017.
Information regarding the data extracted:
The data has been extracted querying the 'Posts' collection through the JSON format:
{"tags" : "ita", "created" : {"$gte" : {"$date":"2017-01-01T00:00:00.00Z"},"$lt" : {"$date":"2018-01-01T00:00:00.00Z"}}}
and filtered only on the fields:
{"author" : true, "net_votes" : true, "curator_payout_value" : true, "total_payout_value" : true, "active_votes" : true, "created" : true, "tags" : true}
The data extracted contained 6271 distinct posts with the #ita tag. The graph below shows the number of distinct post by month. From January to May 2017 the #ita is completely absent in the dataset. The first two posts appears in June and, after that month, there is a steady growth of the number of posts each month to reach 2045 posts in December.
In the considered timeseries, all the published posts have raised 586773 votes. The number of votes received by each post has been aggregated by month and it is showed in the graph below.
Another important metric for the judjement of the posts' trend is the total payout value harvested. All the posts combined have received 85802.43 $, ranging from a minimum of 0 to a maximum of 304.624 $ each with a mediam amount of 5.45 $. The monthly aggregated trend is represented in the graph below.
Another interesting relationship, between the total payout amount against the number of votes, is showed in the scatterplot below. As a reminder, the retrieve amount of author and curator rewards stored on the stemmata mongoDB are expressed as $ (STEEM Token Unit).
Finally, the combination of the Author payout and the Curation Payout, analysed with a simple linear model, shows that the Curation payout is predictable around the 30% of the Author payout.
Collectively, 433 different authors used the tag ita during the 2017. The trend line of the distinct authors by month shows an initial situation with zero authors for the first five months (from January to May), followed by a steep climb from the only two authors in June, to the 50 in July, 92 in August, 126 in September, 144 in October, 157 in November to finally reach 264 distinct authors in the month of December 2017.
The average number of post by author each month goes from 1.5 in June to 8 in September where it stays stable around this value.
Interestingly, the average number of posts by author for each month masks the real distribution of values. In the boxplot below there is the actual distribution of posts by the different authors with an high deviation above the average for some of the most frequent writers. The general trend, excluded the extreme outliers shows that usually the bulk of authors posts less than 40 post each month.
Further investigating into the posting behaviour, it is possible to see the individual median number of posts within the timeframe from June to December. The histogram below show the distribution of the individual median number of posts.
This distribution can be sliced in three main groups. The first is composed of the majority of authors that have an individual posting median of less than 1 (239 Authors), the second from 1 to 10 (169 Authors) and the third for authors that have posted more than 10 times (25 Authors) each month between June and December 2017.
The italian tag ita has born exactly the 28 June 2017 at 09:57:06 with the post made by the author 
The top ten of the most proficient authors has 
The top ten list of the most voted authors has 
Instead the grow in the author payout collected has been extremely high in the last month of the analysis, going from 10000 $ in November to more than 37000 $ in December.
The top ten list of the most rewarded author has 
The relation between the author payout and the number of votes is complex and will need further analyses to be understood in some way.
Since the direct causality given by the rule of the 75/25 reward allocation, the relation between the author and the curator payout is the most foreseeable. However, despite the bulk of rewards is within the 0-25% range, the actual distribution of the curation reward values shows some low outliers just a little above the 25% but stille below 30% but some really high outliers near the 100% that will need some further analysis to understand how that could even be possible.