I'm afraid statistics is not done that way. Sample size calculation involves three groups of component:
The designated chance of calling a statistical significance while in fact there isn't any, known as type I error. It's conventionally set at 5% and it's related to the p-value < 0.05 threshold. Additionally, the other is the designated chance of missing a statistical significance while in fact there is one, known as type II error. It's conventionally set at 20%. The chance of not committing a type II error is called "power" and if type II error rate is 20%, power is 80%.
The second component is called the "effect size." It comes in many shapes and forms but generally it's the strength of association or magnitude of difference you wish to use the statistics to show if such phenomenon is likely a fluke or not.
The third component is the sample size.
In order to make a decision on any one of these three, the other two need to be known (or assumed). So, generally a question on sample size would be something like:
How many samples do I need to detect a difference of 10 units or more (with a
SD of 7.5 units) in total blood cholesterol between the mice fed with low-fat diet and the mice
fed with control diet, with type I error rate set at 5% and power at
80%? And I'd like the ratio of test to control be 1:1.
Then statisticians would be able to help you. Currently, your question does not have effect sizes. (What does "evaluate the significance of each topic" actually measure? Do you mean chance of being downloaded? Viewed? Cited? Funded?) And it does not have the declared error rates. So, it's unlikely for anyone to come up with a sample size.