Assessing Social License to Operate from the Public Discourse on Social Media

Chang Xu, Cecile Paris, Ross Sparks, Surya Nepal, Keith VanderLinden

Abstract
Organisations are monitoring their Social License to Operate (SLO) with increasing regularity. SLO, the level of support organisations gain from the public, is typically assessed through surveys or focus groups, which require expensive manual efforts and yield quickly-outdated results. In this paper, we present SIRTA (Social Insight via Real-Time Text Analytics), a novel real-time text analytics system for assessing and monitoring organisations’ SLO levels by analysing the public discourse from social posts. To assess SLO levels, our insight is to extract and transform peoples’ stances towards an organisation into SLO levels. SIRTA achieves this by performing a chain of three text classification tasks, where it identifies task-relevant social posts, discovers key SLO risks discussed in the posts, and infers stances specific to the SLO risks. We leverage recent language understanding techniques (e.g., BERT) for building our classifiers. To monitor SLO levels over time, SIRTA employs quality control mechanisms to reliably identify SLO trends and variations of multiple organisations in a market. These are derived from the smoothed time series of their SLO levels based on exponentially-weighted moving average (EWMA) calculation. Our experimental results show that SIRTA is highly effective in distilling stances from social posts for SLO level assessment, and that the continuous monitoring of SLO levels afforded by SIRTA enables the early detection of critical SLO changes.
Anthology ID:
2020.coling-industry.14
Volume:
Proceedings of the 28th International Conference on Computational Linguistics: Industry Track
Month:
December
Year:
2020
Address:
Online
Editors:
Ann Clifton, Courtney Napoles
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
146–159
Language:
URL:
https://aclanthology.org/2020.coling-industry.14
DOI:
10.18653/v1/2020.coling-industry.14
Bibkey:
Cite (ACL):
Chang Xu, Cecile Paris, Ross Sparks, Surya Nepal, and Keith VanderLinden. 2020. Assessing Social License to Operate from the Public Discourse on Social Media. In Proceedings of the 28th International Conference on Computational Linguistics: Industry Track, pages 146–159, Online. International Committee on Computational Linguistics.
Cite (Informal):
Assessing Social License to Operate from the Public Discourse on Social Media (Xu et al., COLING 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-5/2020.coling-industry.14.pdf
PDF Search