MY PROBLEM: I need to test for statistical significance between the three groups. The problem comes when extremely large numbers are involved and the chi-square test is always significant. I read several related questions however I didn't find a solution. What test should I use?
- How to test for a statistically significant difference between 3 percentages?
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- How to test for a statistically significant difference between multiple unbalanced groups
MY DATA: We classify tweets into three different groups if the account is: bot/non-bot/self-declared. Then each of the tweets is classified into 18 different topics. We need to check if there are topics where tweets sent by accounts classified as bots (or non-bots or self-declared) are more common.
The total number of tweets written from each of the groups is:
- Bot 1,106,255
- Non-Bot 8,218,070
- Self Declared 1,101,219
For Topic 14 and Topic 9 the distribution is as follows:
| Bot | Non-Bot | Self-Declared | |
|---|---|---|---|
| Topic 14 | 23234 | 192319 | 27585 |
| No Topic 14 | 1083021 | 8025751 | 1073634 |
| Percentage | 2.1% | 2.4% | 2.6% |
| Topic 9 | 117259 | 940800 | 181543 |
| No Topic 9 | 988996 | 7277270 | 919676 |
| Percentage | 11.9% | 12.9% | 19.7% |
Following this method, we plotted this chart 
: