Pie Chart or Pizza: Identifying Chart Types and Their Virality on Twitter
Pie Chart or Pizza: Identifying Chart Types and Their Virality on Twitter
复制标题
DOI：
10.1609/icwsm.v14i1.7335
复制
发表时间：
2020-05
期刊：
影响因子：
--
通讯作者：
P. Vougiouklis;L. Carr;E. Simperl
中科院分区：
文献类型：
--
作者：
P. Vougiouklis;L. Carr;E. Simperl
我们的目标是了解数据如何以图表或信息图表的形式在社交媒体上“传播”。为此，我们提出了一种神经网络架构，该架构经过训练可以区分不同类型的图表，例如线图或散点图，并预测它们将被共享多少。由于所张贴图表的格式和质量各不相同，而且现有培训数据存在局限性，这就带来了重大挑战。首先，我们提出的系统优于相关的工作，在图表类型分类的ReVision语料库。此外，我们使用众包来构建一个新的语料库，更适合我们的目标，由数据记者在Twitter上分享的图表图像组成。我们评估我们的系统在第二个语料库方面的图表识别和病毒性预测，有希望的结果。
We aim to understand how data, rendered visually as charts or infographics, “travels” on social media. To do so we propose a neural network architecture that is trained to distinguish among different types of charts, for instance line graphs or scatter plots, and predict how much they will be shared. This poses significant challenges because of the varying format and quality of the charts that are posted, and the limitations in existing training data. To start with, our proposed system outperforms related work in chart type classification on the ReVision corpus. Furthermore, we use crowdsourcing to build a new corpus, more suitable to our aims, consisting of chart images shared by data journalists on Twitter. We evaluate our system on the second corpus with respect to both chart identification and virality prediction, with promising results.