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arXiv 1603.02604cs.CL
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观察自动化多语言媒体分析的趋势

Observing Trends in Automated Multilingual Media Analysis

European Commission – Joint Research Centre (JRC)(欧盟委员会联合研究中心)

Ralf Steinberger, Aldo Podavini, Alexandra Balahur, Guillaume Jacquet, Hristo Tanev, Jens Linge, Martin Atkinson, Michele Chinosi, Vanni Zavarella, Yaniv Steiner, Erik van der Goot

摘要:

任何大型组织,无论是公共组织还是私营组织,都对媒体进行信息监测,以了解其感兴趣领域的最新发展,通常也了解对媒体的正面或负面意见。至少对于书面媒体来说,计算机程序已经变得非常有效,通过收集媒体报道,分析它们,检测趋势,甚至在某些情况下,发布早期预警或对可能的未来发展做出预测,大大帮助人类分析师完成监测任务。我们在这里介绍欧洲媒体监测(EMM)系统的趋势分析相关功能,该系统由欧盟委员会联合研究中心(JRC)为欧盟(EU)及其他地区的公共行政部门开发。EMM以多达70种语言进行大规模媒体分析,并识别各种类型的趋势,其中一些趋势结合了来自不同语言的新闻文章和社交媒体帖子的信息。EMM还允许用户通过交互式地图和图表探索大量的多语言媒体数据,使他们能够从不同的角度和根据多个标准来检查数据。EMM的许多功能都可以通过互联网或手持设备的应用程序免费访问。

英文摘要:

Any large organisation, be it public or private, monitors the media for information to keep abreast of developments in their field of interest, and usually also to become aware of positive or negative opinions expressed towards them. At least for the written media, computer programs have become very efficient at helping the human analysts significantly in their monitoring task by gathering media reports, analysing them, detecting trends and - in some cases - even to issue early warnings or to make predictions of likely future developments. We present here trend recognition-related functionality of the Europe Media Monitor (EMM) system, which was developed by the European Commission's Joint Research Centre (JRC) for public administrations in the European Union (EU) and beyond. EMM performs large-scale media analysis in up to seventy languages and recognises various types of trends, some of them combining information from news articles written in different languages and from social media posts. EMM also lets users explore the huge amount of multilingual media data through interactive maps and graphs, allowing them to examine the data from various view points and according to multiple criteria. A lot of EMM's functionality is accessibly freely over the internet or via apps for hand-held devices.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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