A New Approach to Generate a Visual Tweet From Text Message

A New Approach to Generate a Visual Tweet from Text Message Hang-Bong Kang Dept. of Digital Media The Catholic University of Korea #43-1 Yokkok 2-dong Wonmi-Gu Bucheon Gyonggi-Do, Korea [email protected] Sang-Hyun Cho Dept. of Computer Engineering, The Catholic University of Korea #43-1 Yokkok 2-dong Wonmi-Gu Bucheon Gyonggi-Do, Korea [email protected] Il-Whang Byun Dept. of Digital Media The Catholic University of Korea #43-1 Yokkok 2-dong Wonmi-Gu Bucheon Gyonggi-Do, Korea [email protected] ABSTRACT In this paper, we propose a new augmented communication method, called visual twitter, for the short messaging system. Particularly, in Twitter, text-based tweets in the limit of 140 characters are efficiently used in communicating with followers, but sometimes are not long enough to clearly express the author ’ s own feeling or emotions. To deal with the author ’ s feelings, we suggest enhancing a text tweet with an appropriate image, along with/without text. To generate an image from the text, we first analyze the text tweet. The morpheme analyzer detects the key words and then the thumbnail images related to those keywords are retrieved. The author can select appropriate images for background, avatars and objects. An intermediate image is then generated. After that, our emotion classifier determines the author ’ s feeling in the text tweet using SVM (Support Vector Machine). Based on the emotion in the tweet, we use our own re-coloring method on the generated image. Our augmented visual communication method is implemented on the smart phone and the author can post her own visual tweet with or without text. The survey result shows that our method of generating visual tweets was favorable and users found the function enjoyable. KEYWORDS: twitter, visual tweets, emotion 1. INTRODUCTION Recently, social networking services such as Twitter, Facebook and Myspace have gained popularity worldwide [1, 2, 3]. In particular, many people who want to broadcast what they are doing to their followers like Twitter because it enables its users to exchange short messages in the form of tweets in the PC and mobile environment. Even though text-based tweets are useful in communicating with followers, it is not always easy for users to express their feelings or emotions within 140 characters limit. For example, if the user wants to post his feeling about lunch or his feelings about the place he visited, the text message is not always long enough to vividly express his opinions. In addition, when text tweets are delivered to foreign followers with different native languages, the language barrier could lead to miscommunication [4]. To compensate for these shortcomings, it is beneficial to add a visual image in order to illustrate the text on the tweet. For a new augmented communication method in the short messaging system, it is necessary to generate an image that is easily attainable. Because a visual image can use three key components such as avatars, objects and background, it is necessary to find a method for connecting the text to the image. Using the morpheme analyzer, we detect key words which can be avatars, objects and backgrounds. However, the text tweets sometimes do not obey grammar rules and sometimes special characters like emoticons are also used in the tweets. Thus, it is necessary to handle those kinds of abnormalities in the text tweets. After that, the author can generate an intermediate image using these components. In order to make sure that the intermediate image correctly reflects what is being said, it is desirable to detect the emotional language found in the text. To classify the emotion, an emotion-related feature vector is computed and then the emotion is classified by the emotion classifier. We use the Support Vector Machine (SVM) in order to determine the author ’s feelings from text tweet. 978-1-61284-639-2/11/$26.00 ©2011 IEEE 265

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A New Approach to Generate a Visual Tweet From Text Message