analytics

library(stringr) library(readr) library(tidyverse) library(lubridate) I have been curious on what makes an interesting post on instagram based on a larger dataset of images that have been tagged with #generativeart. Some of this is just data discovery, this could seem that there may be a correlation between the tags that have been used and the amount of likes there are. # Extract hashtags patt <- regex("#\\S+") genart <- read_csv("~/InstaCrawlR/table-generativeart-2020-10-11 13:35:33.csv") genart_db <- genart %>% select(ID, Likes, Owner, Date, Text) %>% mutate(hashtags = str_extract_all(Text,patt) ) genart_db_table <- genart_db %>% unnest(cols = "hashtags") %>% mutate(Year = year(Date), Month = month(Date), DayOfWeek = wday(Date), Day = day(Date), Hour = hour(Date)) genart_db_table %>% head() That will generate a rather large dataset...

Fraud continues to be an important topic in the financial world helping detect when funds are mismanaged. Nilson reports that U.S. card fraud (credit, debt, etc) was reportedly $9 billion in 2016 and expected to increase to $12 billion by 2020. Due to these nefarious acts; it is in the best interest of any organization to ensure the work of most customers. Thus it is appropriate to respond to this fraud....