The present invention provides a system comprising a user interface configured to receive text input by a user, a text prediction engine comprising a plurality of language models and configured to receive the input text from the user interface and to generate concurrently text predictions using the plurality of language models, and wherein the text prediction engine is further configured to provide text predictions to the user interface for display and user selection. An analogous method and an interface for use with the system and method are also provided.

System and method for inputting text into electronic devices

Recent years have witnessed the explosive growth of online social media. Weibo, a Twitter-like online social network in China, has attracted more than 300 million users in less than three years, with more than 1000 tweets generated in every second. These tweets not only convey the factual information, but also reflect the emotional states of the authors, which are very important for understanding user behaviors. However, a tweet in Weibo is extremely short and the words it contains evolve extraordinarily fast. Moreover, the Chinese corpus of sentiments is still very small, which prevents the conventional keyword-based methods from being used. In light of this, we build a system called MoodLens, which to our best knowledge is the first system for sentiment analysis of Chinese tweets in Weibo. In MoodLens, 95 emoticons are mapped into four categories of sentiments, i.e. angry, disgusting, joyful, and sad, which serve as the class labels of tweets. We then collect over 3.5 million labeled tweets as the corpus and train a fast Naive Bayes classifier, with an empirical precision of 64.3%. MoodLens also implements an incremental learning method to tackle the problem of the sentiment shift and the generation of new words. Using MoodLens for real-time tweets obtained from Weibo, several interesting temporal and spatial patterns are observed. Also, sentiment variations are well captured by MoodLens to effectively detect abnormal events in China. Finally, by using the highly efficient Naive Bayes classifier, MoodLens is capable of online real-time sentiment monitoring. The demo of MoodLens can be found at http://goo.gl/8DQ65.

http://jpkc.fudan.edu.cn/picture/article/81/f2/99/5a4dcd89499eba2b4caf15d45755/0e4cf37c-3913-4b0a-be21-18c314228c05.pdf

MoodLens: an emoticon-based sentiment analysis system for chinese tweets

Recent years have witnessed the tremendous growth of the online social media. In China, Weibo, a Twitter-like service, has attracted more than 500 million users in less than five years. Connected by online social ties, different users might share similar affective states. We find that the correlation of anger among users is significantly higher than that of joy. While the correlation of sadness is surprisingly low. Moreover, there is a stronger sentiment correlation between a pair of users if they share more interactions. And users with larger number of friends possess more significant sentiment correlation with their neighborhoods. Our findings could provide insights for modeling sentiment influence and propagation in online social networks.

/pdf/anger-is-more-influential-than-joy-sentiment-correlation-in-2k953z697n.pdf

Anger Is More Influential than Joy: Sentiment Correlation in Weibo

There is a difference between the optimal rates of fixed-length source coding and intrinsic randomness when we care about the second-order asymptotics. We prove this difference for general information sources and then investigate independent and identically distributed (i.i.d.) random variables and Markovian variables as examples. The difference is demonstrated through an investigation of the second-order asymptotic behavior of the rates. A universal fixed-length source code attaining the second-order optimal rate is also proposed. The difference between the rates of fixed-length source coding and intrinsic randomness proves that the outputs of fixed-length source codes are not uniformly distributed.

Second-Order Asymptotics in Fixed-Length Source Coding and Intrinsic Randomness

A growing body of research explores emoji, which are visual symbols in computer mediated communication (CMC). In the 20 years since the first set of emoji was released, research on it has been on the increase, albeit in a variety of directions. We reviewed the extant body of research on emoji and noted the development, usage, function, and application of emoji. In this review article, we provide a systematic review of the extant body of work on emoji, reviewing how they have developed, how they are used differently, what functions they have and what research has been conducted on them in different domains. Furthermore, we summarize directions for future research on this topic.

/pdf/a-systematic-review-of-emoji-current-research-and-future-46phb8j6fk.pdf

A Systematic Review of Emoji: Current Research and Future Perspectives.

In this paper, we propose a new information theoretic method called structural information control for flexible feature discovery. The new method has three distinctive characteristics, which traditional competitive learning fails to offer. First, the new method can directly control competitive unit activation patterns, whereas traditional competitive learning does not have any means to control them. Thus, with the new method, it is possible to extract salient features not discovered by traditional methods. Second, competitive units compete witheach other by maximizing their information content about input patterns. Consequently, this information maximization makes it possible to control flexibly competition processes. Third, in structural information control, it is possible to define many different kinds of information content, and we can choose a specific type of information according to a given objective. When applied to competitive learning, structural information can be used to control the number of d...

Flexible feature discovery and structural information control

In recent years, reputation analysis services using weblogs, message boards, and community web sites have been developed. To improve the accuracy of the reputation analysis, we have to extract emotions or reactions of writers of documents accurately. Emoticons (Emojis) are often used in weblogs, and in many cases these emoticons have the role of modalities of writers of weblog articles. That is, to estimate emotions represented by emoticons is important for reputation analysis. In this study, we propose a method to create emotional vectors of emoticons automatically using the collocation relationship between emotional words and emoticons which is derived from many weblog articles.

A method for automatically generating the emotional vectors of emoticons using weblog articles

A Real-Time Information Sharing System to Support Self-, Mutual-, and Public-Help in the Aftermath of a Disaster Utilizing Twitter

In variable-length coding, the probability of codeword length per source letter being above (resp. below) a prescribed threshold is called the overflow (resp. the underflow) probability. In this study, we show that the infimum achievable threshold given the overflow probability exponent r always coincides with the infimum achievable fixed-length coding rate given the error exponent r, without any assumptions on the source. In the case of underflow probability, we also show the similar results. From these results, we can utilize various theorems and results on the fixed-length coding established by Han for the analysis of overflow and underflow probabilities.

The Optimal Overflow and Underflow Probabilities of Variable-Length Coding for the General Source

We show that an optimal source code with a cost function for code symbols can be regarded as a random number generator generating a random sequence (not necessarily a sequence of fair coin bits) as the target distribution in the sense that the normalized conditional divergence between the distribution of the generated codeword distribution and the target distribution vanishes as the block length tends to infinity.

/pdf/source-code-with-cost-as-a-nonuniform-random-number-2tn891fvwy.pdf

Osamu Uchida

Papers

Flexible feature discovery and structural information control

A method for automatically generating the emotional vectors of emoticons using weblog articles

A Real-Time Information Sharing System to Support Self-, Mutual-, and Public-Help in the Aftermath of a Disaster Utilizing Twitter

The Optimal Overflow and Underflow Probabilities of Variable-Length Coding for the General Source

Source code with cost as a nonuniform random number generator