Subtopic Deep Dive

Stakeholder Engagement in Crisis Management
Research Guide

What is Stakeholder Engagement in Crisis Management?

Stakeholder engagement in crisis management involves dialogic communication strategies used by organizations to build relationships, gather feedback, and foster collaboration with stakeholders like employees, communities, and regulators during crises.

Researchers analyze two-way communication on platforms like Twitter and TikTok to engage publics during disasters and pandemics. Lovejoy and Saxton (2012) identified three Twitter functions—information, community, action—with 861 citations. Over 10 papers from 2012-2021, cited 100-800+ times, examine social media's role in crises including COVID-19 and Typhoon Haiyan.

15
Curated Papers
3
Key Challenges

Why It Matters

Effective stakeholder engagement via social media builds trust and drives supportive behaviors during crises, as Kang (2014) modeled its influence on intentions (189 citations). Governments and nonprofits use these strategies for risk communication, seen in Hyland et al. (2021, 470 citations) on COVID-19 messaging and Takahashi et al. (2015, 374 citations) on disaster tweets. Outcomes include faster recovery, reduced misinformation, and long-term relationship resilience, applied in public health emergencies and natural disasters.

Key Research Challenges

Measuring Engagement Impact

Quantifying how engagement leads to behavioral changes remains difficult due to lacking standardized metrics. Kang (2014) operationalized engagement at individual levels but called for macro-level tests (189 citations). Studies like Lovejoy and Saxton (2012) highlight action-oriented tweets yet struggle with causal links (861 citations).

Misinformation in Social Media

Crises amplify rumors on platforms like Twitter, complicating trust-building. Abd-Alrazaq et al. (2020) analyzed top COVID-19 tweet concerns, revealing infoveillance needs (830 citations). Panagiotopoulos et al. (2016) noted risks in emergency Twitter use (253 citations).

Platform Algorithm Variability

Shifting algorithms affect message reach to diverse stakeholders. Li et al. (2021) content-analyzed TikTok COVID videos, showing format dependencies (243 citations). Castelló et al. (2013) discussed polyphonic CSR dynamics in networks (149 citations).

Essential Papers

1.

Information, Community, and Action: How Nonprofit Organizations Use\n Social Media

Lovejoy, Kristen, Saxton, Gregory D. · 2012 · arXiv (Cornell University) · 861 citations

The rapid diffusion of "microblogging" services such as Twitter is ushering\nin a new era of possibilities for organizations to communicate with and engage\ntheir core stakeholders and the general ...

2.

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study

Alaa Abd‐Alrazaq, Dari Alhuwail, Mowafa Househ et al. · 2020 · Journal of Medical Internet Research · 830 citations

Background The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world’s health care infrastructure as well as the social, economic, and psychological well-being of humanity. I...

3.

Toward effective government communication strategies in the era of COVID-19

Bernadette Hyland, John Gardner, Julie Leask et al. · 2021 · Humanities and Social Sciences Communications · 470 citations

4.

Communicating on Twitter during a disaster: An analysis of tweets during Typhoon Haiyan in the Philippines

Bruno Takahashi, Edson C. Tandoc, Christine Carmichael · 2015 · Computers in Human Behavior · 374 citations

5.

Climate Change Sentiment on Twitter: An Unsolicited Public Opinion Poll

Emily M. Cody, Andrew J. Reagan, Lewis Mitchell et al. · 2015 · PLoS ONE · 294 citations

The consequences of anthropogenic climate change are extensively debated through scientific papers, newspaper articles, and blogs. Newspaper articles may lack accuracy, while the severity of findin...

6.

Social media in emergency management: Twitter as a tool for communicating risks to the public

Panos Panagiotopoulos, Julie Barnett, Ali Ziaee Bigdeli et al. · 2016 · Technological Forecasting and Social Change · 253 citations

7.

Communicating COVID-19 information on TikTok: a content analysis of TikTok videos from official accounts featured in the COVID-19 information hub

Yachao Li, Mengfei Guan, Paige Hammond et al. · 2021 · Health Education Research · 243 citations

Abstract Amid the COVID-19 pandemic, TikTok, an emerging social media platform, has created an information hub to provide users with engaging and authoritative COVID-19 information. This study inve...

Reading Guide

Foundational Papers

Start with Lovejoy and Saxton (2012, 861 citations) for Twitter's information-community-action framework in stakeholder communication, then Kang (2014, 189 citations) for engagement measurement models.

Recent Advances

Study Hyland et al. (2021, 470 citations) on COVID government strategies and Li et al. (2021, 243 citations) on TikTok formats for modern platform insights.

Core Methods

Content analysis of posts (Takahashi et al., 2015), sentiment polling (Cody et al., 2015), infoveillance (Abd-Alrazaq et al., 2020), and trust-repair discourse (Fuoli and Paradis, 2014).

How PapersFlow Helps You Research Stakeholder Engagement in Crisis Management

Discover & Search

Research Agent uses searchPapers and exaSearch to find high-citation works like Lovejoy and Saxton (2012, 861 citations) on nonprofit Twitter engagement, then citationGraph reveals clusters around COVID-19 communication from Hyland et al. (2021). findSimilarPapers expands to related crisis tweets like Takahashi et al. (2015).

Analyze & Verify

Analysis Agent applies readPaperContent to extract engagement models from Kang (2014), verifies claims with CoVe chain-of-verification, and runs PythonAnalysis on tweet data for sentiment stats using pandas. GRADE grading scores evidence strength in social media crisis studies.

Synthesize & Write

Synthesis Agent detects gaps in two-way communication outcomes across papers, flags contradictions in Twitter vs. TikTok efficacy. Writing Agent uses latexEditText, latexSyncCitations for Kang (2014) and Lovejoy (2012), latexCompile for reports, exportMermaid for stakeholder feedback loop diagrams.

Use Cases

"Analyze sentiment in COVID-19 stakeholder tweets from top papers"

Research Agent → searchPapers('COVID-19 Twitter engagement') → Analysis Agent → runPythonAnalysis(pandas sentiment on Abd-Alrazaq et al. 2020 data) → matplotlib plots of concern trends.

"Draft LaTeX review on Twitter crisis strategies citing Lovejoy 2012"

Research Agent → citationGraph(Lovejoy 2012) → Synthesis → gap detection → Writing Agent → latexEditText(structured review) → latexSyncCitations(10 papers) → latexCompile(PDF output).

"Find GitHub repos analyzing crisis tweet datasets"

Research Agent → paperExtractUrls(Takahashi 2015) → Code Discovery → paperFindGithubRepo → githubRepoInspect → runPythonAnalysis(replicate typhoon tweet models).

Automated Workflows

Deep Research workflow scans 50+ papers via searchPapers on 'stakeholder Twitter crisis', structures reports with engagement metrics from Kang (2014). DeepScan's 7-step chain verifies social media claims with CoVe on Hyland et al. (2021), includes GRADE checkpoints. Theorizer generates dialogic theory from Lovejoy (2012) and Takahashi (2015) abstracts.

Frequently Asked Questions

What defines stakeholder engagement in crisis management?

It uses dialogic strategies for two-way communication with stakeholders during crises, as conceptualized by Kang (2014) at individual levels influencing behaviors (189 citations).

What methods analyze social media engagement?

Content analysis of tweets (Takahashi et al., 2015, 374 citations) and infoveillance of concerns (Abd-Alrazaq et al., 2020, 830 citations) measure information, community, action functions (Lovejoy and Saxton, 2012).

What are key papers?

Lovejoy and Saxton (2012, 861 citations) on nonprofit Twitter; Kang (2014, 189 citations) on engagement models; Hyland et al. (2021, 470 citations) on government COVID strategies.

What open problems exist?

Causal measurement of engagement outcomes, misinformation mitigation (Panagiotopoulos et al., 2016), and algorithm impacts on reach remain unresolved.

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