ABSTRACT The amount of opinionated data on the web has exponentially increased especially after the emergence of online social networks. To deal with these huge deluge of data, we need to have robust mechanisms that can help identify all aspects of opinion segment and support the automatic processing of opinion data. Recently, there have been a few developments made in this direction, and different sentiment annotation schemes have been proposed such as the SentiML, OpinionMiningML, and EmotionML. In this work, we propose SentiML++, an extension of SentiML with a focus on annotating opinions, and further answering aspects of the general question “who has what opinion about whom in which context?”. A detailed comparison with SentiML and other existing annotation schemes is also presented. The data collection annotated with SentiML has been annotated with SentiML++ and is available for download for further research purposes. Experiments with data collections annotated with SentiML and SentiML++ proves that SentiML++ is a significant and valuable addition to SentiML.

中文翻译：

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SentiML ++：SentiML 情感标注方案的扩展

摘要 网络上自以为是的数据量呈指数增长，尤其是在在线社交网络出现之后。为了应对这些海量的数据，我们需要有强大的机制来帮助识别意见片段的各个方面，并支持意见数据的自动处理。最近，在这个方向上取得了一些进展，并提出了不同的情感标注方案，如 SentiML、OpinionMiningML 和 EmotionML。在这项工作中，我们提出了 SentiML++，它是 SentiML 的扩展，专注于注释意见，并进一步回答一般问题“谁在什么情况下对谁有什么意见？”的各个方面。还介绍了与 SentiML 和其他现有注释方案的详细比较。用 SentiML 注释的数据集合已用 SentiML++ 注释，可供下载以供进一步研究。对使用 SentiML 和 SentiML++ 注释的数据集合进行的实验证明，SentiML++ 是 SentiML 的重要且有价值的补充。