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.

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 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

Twitter as a tool for the management and analysis of emergency situations: A systematic literature review

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

Utilizing Twitter at the time of accidents has been gaining attention, because to minimize the damage in case of a disaster, it is important to collect and spread accurate information quickly To support information sharing in the aftermath of a disaster utilizing Twitter, Uchida et al proposed a Twitter-based disaster-related information sharing system which is consisting of two subsystems; DITS (Disaster Information Tweeting System) and DIMS (Disaster Information Mapping System) However, there are several problems on the system Foe example, there were cases where incorrect tweet mapping, which is problematic in practical use, occurred Therefore, in this study, we try to improve the system

Improvement of Twitter-based disaster-related information sharing system

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 with variable-length coding for the general source

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

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Osamu Uchida

Author Tools

Chat about Author