With its rising popularity, as evidenced in social networks, online shopping platforms and email systems, detection of Web spammer has already become one of the hottest topics in the data mining field. The main challenge of Web spammer detection is how to recognize spammer behavior patterns by examining spammer features and attributes from big dataset in order to limit the proliferation of Internet spam and insure quality of Internet service. This paper presents an overview of Web spammer detection, along with a comparison over the difference between traditional and burgeoning spammer detection approaches. The key techniques and evaluation methods are classified and discussed from several aspects. At last, the prospects for future development and suggestions for possible extensions are emphasized.