Virtual communities are the uppermost communication spaces and channels for online word-of-mouth. And opinion leaders are the most important group for enterprises’ word-of-mouth communication. As enterprises are engaged in online word-of-mouth marketing activities, the key is to find out the opinion leaders in virtual communities. In this paper, after affirming the effects of opinion leaders an...

For every symmetric (“palindromic”) word S(A,B) in two positive definite letters and for each fixed n-by-n positive definite B and P , it is shown that the symmetric word equation S(A,B) = P has an n-by-n positive definite solution A. Moreover, if B and P are real, there is a real solution A. The notion of symmetric word is generalized to allow non-integer exponents, with certain limitations. I...

We introduce a novel mixed characterword architecture to improve Chinese sentence representations, by utilizing rich semantic information of word internal structures. Our architecture uses two key strategies. The first is a mask gate on characters, learning the relation among characters in a word. The second is a maxpooling operation on words, adaptively finding the optimal mixture of the atomi...

The word length effect-lhe finding that lislsofshort words are beuer recalledlhanlists of long words-has been termed one of the benchmark findings that any theory of immediate memory must address. The effect is viewed as the best remaining evidence for time-based decay of information in short-term memory. However, previous studies invesligating this effecl have confounded word length withorthog...

This paper explores the relative contributions made by orthography, syllabic segment, and lexical tone in the word recognition and retrieval process. It also challenges recent assumptions regarding the role of orthography and tones in mental lexicon architecture. Using an implicit priming paradigm, a word recognition experiment was conducted with native speakers of two tonal languages, Chinese ...

In this article, we use an automated bottom-up approach to identify semantic categories in an entire corpus. We conduct an experiment using a word vector model to represent the meaning of words. The word vectors are then clustered, giving a bottom-up representation of semantic categories. Our main finding is that the likelihood of changes in a word’s meaning correlates with its position within ...

Cross-linguistic studies on unsupervised word segmentation have consistently shown that English is easier to segment than other languages. In this paper, we propose an explanation of this finding based on the notion of segmentation ambiguity. We show that English has a very low segmentation ambiguity compared to Japanese and that this difference correlates with the segmentation performance in a...

In two experiments, subjects studied lists of categorized words and then were tested for recognition of those words. Response time for a test word was speeded whenever the immediately preceding test word was from the same category. This was true even for test words (lures) from categories never studied. Thus it is argued that semantic information not present at the time of study affected retrie...

A novel method based on Wikipedia for clustering keyword of reviews is proposed. Users can quickly finding the themes they interest through it. First the method extracts keywords, then calculates word similarity based on Wikipedia to generate similarity matrix, finally uses k-means to cluster. The performance is better than the methods which based on How-net and Word-net. The accuracy is around...

Cross-linguistic studies on unsupervised word segmentation have consistently shown that English is easier to segment than other languages. In this paper, we propose an explanation of this finding based on the notion of segmentation ambiguity. We show that English has a very low segmentation ambiguity compared to Japanese and that this difference correlates with the segmentation performance in a...