Schedule

Presentation 1

Time: 12:00 - 12:30

Speaker: Assem Dandashly

Title: The Power of Emotions and Sensemaking in leaders' discourse: Unsupervised machine learning of Hassan Nasrallah's public speeches, 2015-2022

Abstract: 
Since its creation in 1982, Hezbollah has evolved from a resistance group and local militia participating in the Lebanese civil war (1980s) to a highly influential hybrid political group, extending its influence beyond Lebanon. Over the years, Hezbollah actively promoted charity and religious education welfare to its Shiite supporters, to whom it provides a political home that represents their interests in Lebanon's domestic and foreign policy making. With its continuous struggle against Israel and involvement in conflicts with various groups in Syria and Iraq, the organization gained further influence as a formidable power protecting Lebanon and deterring its enemies. Hezbollah's geopolitical scope extends beyond Lebanon and its neighboring countries, and it has been involved in regional conflicts such as the wars in Syria and Yemen, and even internationally with terrorist activities in Latin America and across the globe.
While the positions taken by Nasrallah have grave effects on many in the Middle East and beyond, there has not been, to date, a systematic attempt to understand Nasrallah's discourse and learn about his leadership. The availability of his speeches and new machine-learning methods of analyzing text enable researchers to study his public speeches and gain better understanding of Hezbollah's roles in local and international conflicts.

This paper engages with the literature on leadership and focuses on the emotions and sense making/sense giving in charismatic, ideological and pragmatic (CIP) leadership, focusing on Nasrallah's public speeches. In the first step, we have created an unstructured corpus with all of Nasrallah's 129 speeches delivered between January 2015 and November 2021. Using an unsupervised machine learning latent dirichlet allocation probabilistic model with Gibbs sampling, we find three main findings.
First, despite leading an organization designated as terrorist by many countries in the West and in the Middle East, Nasrallah shows great interest in civic affairs, Lebanese internal politics and current events. Second, despite his own self-admitted commitment to Iran and its regional interests, Nasrallah increasingly proclaims the role of a legitimate Lebanese national leader. Lastly, we study the sense-making/giving and emotions in his speeches using the charismatic-ideological-pragmatic leadership framework and reflect on Nassrallah's leadership.

Presentation 2

Time: 12:30 - 13:00

Speaker: Eliyahu V. Sapir

Title: Can we trust measures of trust? Measurement invariance in trust in EU news media

Abstract: 
Trust in the news media received wide scholarly attention for almost a century, which was further boosted as a result of recent developments in the media landscape and changes in how news is made and consumed. Despite that, the conceptualization of trust in the news media is still debated, and its measurement comparability has not yet been established.

In this paper, I build up on earlier conceptualizations of trust in the news media, and test three theoretically derived measurement models to determine their cross-cultural equivalence in 28 EU countries. Using Eurobarometer data, I test the validity and comparability of these measurements employing multi-group confirmatory factor analysis. The findings indicate that trust is a unidimensional latent construct, equally interpreted across contexts. People's level of trust in the news media reflects their general attitude to the news stories and reporters in all sources of media they are exposed to. While bifactorial measurements of news media trust, differentiating between legacy and online sources, have some merit in single case-studies, they are non-invariant and therefore non comparable. This means that any cross-population differences found employing them are likely a function of measurement idiosyncrasies or other unknown factors.