融媒体语境下数据新闻的多源异构研究

Research on Multi-source Heterogeneity of Data Journalism in the Context of Media Convergence

融媒体时代,数据驱动新闻生产朝着精细化路径发展,日益强调个性化、可视化与社交化。但面对繁杂的大数据,数据新闻似乎仍难以带领新闻业跨越后真相的迷雾:算法逻辑易引发信息失衡与信息歧视,"客观性数据"亦可成为后真相的推手,数据与可视化的简单"嫁接"限制深入报道。如何在多源异构的数据中找到所需数据并高效利用,如何在结构迥异的数据间建立关联,如何通过多结构数据的呈现最大限度地揭示真相,成为数据新闻生产的关键。本文认为未来数据新闻有望从大数据跨源调度、数据融合互通、创新交互可视化这三个方面来突破局限,进一步提升其专业性。

In the era of converging media, data-driven news production is moving towards refinement, which increasingly emphasizes on personalization, visualization and socialization. At the same time, facing multi-source heterogeneous data, it seems that data journalism still cannot lead the news industry to overcome the fog of post-truth.Algorithm logic is prone to information imbalance and information discrimination. "Objective" data may also lead to post-truth.The simple combination of dataand visualization hinders in-depth news reporting.How to find and use the data efficiently among the multi-source heterogeneous data, how to establish the association between the data with different structures, and how to reveal the truth to the greatest extent through the presentation of multi-structure data, become the keys of data journalism production.This paper believes that future data journalism is expected to break through the limitations and further improve its professionalism from three aspects:big data cross-source scheduling, data fusion and interoperability, and innovative interactive visualization.