Microtext are short snippets of text found in many modes of communication: microblogs (e.g., Twitter, Plurk), Short Message Streams (SMS), chat (e.g., instant messaging, Internet Relay Chat), and transcribed conversations (e.g., FBI hostage negotiations). Microtext often has the characteristics of informality,
brevity, varied grammar, frequent misspellings (both accidental and purposeful), and usage of abbreviations, acronyms, and emoticons. With more conversational forms of microtext such as multiparticipant chat, there are also entangled conversation threads. These characteristics create many difficulties for analyzing and understanding microtext, often causing traditional NLP techniques to fail.

Research on microtext is becoming increasingly necessary given the explosion of on-line microtext language. Yet, very few suitable tools have been developed for analyzing it. Also, there are few sufficiently-large publicly-available data sets (such as the Twitter corpus). Currently, most NLP tools are designed to deal with grammatical, properly spelled and punctuated language corpora. However, the reality is that a vast portion of online data does not conform to the canons of standard grammar and spelling.

This symposium will provide a multi-day forum to bring together researchers from different communities who have an interest in analyzing microtext: artificial intelligence, machine learning, computational linguistics, information retrieval, linguistics, human-computer interaction, education, and the social sciences. It will provide enough time for the different communities to present their perspectives and methodologies, to learn one another’s terminology and techniques, and to begin to form connections that will hopefully lead to fruitful collaborations.

Topics:
Topics of interest include, but are not limited to:
* Identification of message characteristics (e.g., relevancy, centrality, repeatability, trustworthiness)
* Creation of participant profile (e.g., age, gender, expertise topics, emotional states, social roles)
* Author attribution
* Topic detection and monitoring
* Topic-to-subtopic decomposition and topic stage evolution tracking and prediction
* Thread summarization
* Modeling of influence and attitude changes
* Corpus creation
* Language structure (e.g., part of speech, dialogue acts, speech acts)
* Visualization

Submissions:
Interested participants should submit papers (8 pages maximum) in AAAI-style (www.aaai.org/Publications/Author/author.php) via https://www.easychair.org/account/signin.cgi?conf=sam2013 .
We welcome papers describing completed work, work-in-progress, interesting ideas even though they may not be completely worked through, and discussion pieces.

Organizing Committee:
Eduard Hovy (USC Information Sciences Institute)
Vita Markman (Disney Interactive Media Group)
Craig Martell (Naval Postgraduate School)
David Uthus (National Research Council and Naval Research Laboratory)