SAP Inside Track Walldorf Social Media Story #sitwdf

[TammyPowlas]

Using the Narrative Science extension with SAP BusinessObjects Lumira, I let "Lumira" tell the story of yesterday's SAP Inside Track Walldorf:

Figure 1:
The analysis compares Counts by Created At (UTC+1h).

Average Counts was 124.8 across all ten periods.

• Counts increased by 1617% over the course of the series from 6 to 103 but unfortunately ended on a disappointing note, decreasing by 772 in 1/15/2017.


• The largest net growth was from 1/8/2017 to 1/14/2017, when Counts rose by 874 (87400%).


• The two periods of consecutive growth from 1/12/2017 to 1/14/2017 when Counts rose by 7855% significantly impacted this net growth. (source: Narrative Science)

Figure 2:
This analysis measures Counts by Time Zone.

Total Counts is 737 across all five entities.

• The distribution ranges from 61 (London) to 390 (Berlin), a difference of 329.


• The average Counts per entity is 147.4 and the median is 96.


• Berlin (390) is almost three times bigger than the average across the five entities, and it is more than four times bigger than the next entity, Amsterdam (97). (Source: Narrative Science)

Figure 3:
This analysis measures Counts by Name.

Total Counts is 404 across all five entities.

• The distribution ranges from 50 (Nagesh Polu) to 187 (JITENDRA KANSAL), a difference of 137.


• The average Counts per entity is 80.8 and the median is 55.


• JITENDRA KANSAL (187) is more than two times bigger than the average across the five entities, and it is more than three times bigger than the next entity, Katarina Fischer (58). (Source: Narrative Science)

Figure 4:
This analysis measures Counts by Source.

Total Counts is 995 across all five entities.

• The minimum value is 61 (TweetDeck) and the maximum is 430 (Twitter for iPhone), a difference of 369.


• The average Counts per entity is 199 and the median is 124.


• Twitter for iPhone (430) is more than two times bigger than the average across the five entities (Source: Narrative Science)

Figure 5:
This analysis measures Counts by Lang.

Total Counts is 1,235 across all six entities.

• The distribution ranges from 9 (it and no) to 919 (en), a difference of 910.


• The average Counts per entity is 205.83 and the median is 25.


• The most common value is 9 which occurred two times.


• Counts is relatively concentrated with 94% of the total represented by two of the six entities (33%).


• On the other hand, the four smallest entities (67% of the total) represent 5.51% of the total Counts.


• En (919) is more than four times bigger than the average across the six entities, and it is almost four times bigger than the next entity, de (248).


• En accounts for 74% of overall Counts.

The most retweeted and favorited tweet was by Frank Koehntopp:


26 retweets, 53 likes.