11,114 research outputs found

    Words are Malleable: Computing Semantic Shifts in Political and Media Discourse

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    Recently, researchers started to pay attention to the detection of temporal shifts in the meaning of words. However, most (if not all) of these approaches restricted their efforts to uncovering change over time, thus neglecting other valuable dimensions such as social or political variability. We propose an approach for detecting semantic shifts between different viewpoints--broadly defined as a set of texts that share a specific metadata feature, which can be a time-period, but also a social entity such as a political party. For each viewpoint, we learn a semantic space in which each word is represented as a low dimensional neural embedded vector. The challenge is to compare the meaning of a word in one space to its meaning in another space and measure the size of the semantic shifts. We compare the effectiveness of a measure based on optimal transformations between the two spaces with a measure based on the similarity of the neighbors of the word in the respective spaces. Our experiments demonstrate that the combination of these two performs best. We show that the semantic shifts not only occur over time, but also along different viewpoints in a short period of time. For evaluation, we demonstrate how this approach captures meaningful semantic shifts and can help improve other tasks such as the contrastive viewpoint summarization and ideology detection (measured as classification accuracy) in political texts. We also show that the two laws of semantic change which were empirically shown to hold for temporal shifts also hold for shifts across viewpoints. These laws state that frequent words are less likely to shift meaning while words with many senses are more likely to do so.Comment: In Proceedings of the 26th ACM International on Conference on Information and Knowledge Management (CIKM2017

    Reading in the Disciplines: The Challenges of Adolescent Literacy

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    A companion report to Carnegie's Time to Act, focuses on the specific skills and literacy support needed for reading in academic subject areas in higher grades. Outlines strategies for teaching content knowledge and reading strategies together

    Science Literacy: Collection of Earth Science Lessons Emphasizing Writing in Science

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    The purpose of this project is to create lessons and projects for high school Earth Science classes encompassing science literacy, specifically focused on writing. With the recent release of the Next Generation Science Standards, science literacy has gained importance in science education. This being said, teachers need the pedagogical skills to implement and teach science literacy. For this project, a literature review of science literacy was conducted which lead to a focus on writing in science. Past research of writing in science classrooms revealed that more than half of high school science teachers claim that they do not feel prepared to teach writing in science nor have the time to do so. The literature review of this thesis highlights the theoretical framework of learning through writing, the four writing strategies and difficulties faced by the teacher and students. The last section of the literature review brings ideas together in a discussion concerning the implementation of writing in a science classroom. The final section of this thesis contains a series of lesson plans and projects developed for a high school Earth Science classroom. To develop the lesson plans four particular writing strategies were utilized. These include RAFT, SWH (science writing heuristic), Cornell notetaking and the Interactive Notebook. The lessons developed incorporate different approaches for writing assignments, including several opportunities for student choice. Writing in science is possible at the high school level. The students’ ability to learn science through writing will be significantly enhanced when they are encouraged and guided by a knowledgeable and dedicated teacher
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