The Support Vector Machine can be viewed as a kernel machine. As a result, you can change its behavior by using a different kernel function.
The most popular kernel functions are :
- the linear kernel
- the polynomial kernel
- the RBF (Gaussian) kernel
- the string kernel
The linear kernel is often recommended for text classification
It is interesting to note that :
The original optimal hyperplane algorithm proposed by Vapnik in 1963 was a linear classifier 
That's only 30 years later that the kernel trick was introduced.
If it is the simpler algorithm, why is the linear kernel recommended for text classification?
Text is often linearly separable
Most of text classification problems are linearly separable