數位化的今天，電影逐漸成為人們日常生活的一部份，電影資料的內涵式分析也成為目前重要的研究主題。透過電影拍攝手法，我們知道電影視聽覺特徵與情緒之間有密不可分的關係。因此，在本研究中，我們希望利用探勘電影視聽覺特徵與情緒的關聯來達到自動判斷電影場景的情緒。 首先，先由人工標記訓練場景的情緒，之後，我們對所有的場景擷取定義的六類特徵值。特徵值包括電影場景的顏色、燈光、影片速度、特寫鏡頭、聲音和字幕六類。最後，我們利用Mixed Media Graph演算法來探勘場景情緒與特徵值之間的關聯，達到自動判斷電影場景情緒的功能。實驗結果顯示，準確率最高可達到70%。 / Movies play an important role in our life nowadays. How to analyze the emotional content of movies becomes one of the major issues. Based on film grammar, there are many audiovisual cues in movies helpful for detecting the emotions of scenes. In this research, we investigate the discovery of the relationship between audiovisual cues and emotions of scenes and the automatic emotion annotation of scenes is achieved. First, the training scenes are labeled with the emotions manually. Second, six classes of audiovisual features are extracted from all scenes. These classes of features consist of color, light, tempo, close-up, audio, and textual. Finally, the graph-based approach, Mixed Media Graph is modified to mine the association between audiovisual features and emotions of the scenes. The experiments show that the accuracy achieves 70%.

Diploma thesis "Principles of popularization of scientific knowledge on the Czech and American news servers" evaluates and compares news published during three month period in scientific sections of news servers in the Czech Republic and the United States of America. The thesis follows room provided for scientific topics, the audiovisual features and theme agenda on NYTimes.com, USAToday.com, iDnes.cz and Novinky.cz. The results are accomplished through the quantitative content analysis which is supplemented by the qualitative semiotic analysis. The semiotic analysis determins compositional and narrative structures and the language features in the articles. It is very important to be concerned about the scientific journalism, as science is important in people's lives and, furthermore, it is the public who helps to support scientific efforts financially. Thus, scientists should be concerned about and aware of science communication in media.