Associating sentimental orientation of Chinese neologism in social media data

Sentiment analysis has always found its practical use in collecting people's preferences towards any subject in the context of social media. Unlike normal words available in dictionaries, neologisms are not easy to be labeled with a sentimental orientation while they have been widely used in conveying people's feelings and opinions. In order to conduct a reliable sentiment analysis for neologisms, a neologism discovery method is first required. Next, a sentimental analysis based on the discovery results can be performed. This paper proposes a 2-step novel solution by having a Chinese neologism discovery method and then a sentimental orientation determination algorithm based on varied TF-IDF. For neologism discovery, statistical data include frequency, duration of appearance and the number of users using a neologism. For sentimental orientation determination, we consider keyword term frequency, and document frequency together and use a varied TF-IDF algorithm. The preliminary experimental results show good precision rate and recall rates for a collection of social media data in both neologism discovery and sentimental analysis.