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.