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Given inconsistent results in prior studies, this paper applies the dual process theory to investigate what social media messages yield audience engagement during a political event. It tests how affective cues (emotional valence, intensity and collective self-representation) and cognitive cues (insight, causation, certainty and discrepancy) contribute to public engagement.

The authors created a dataset of more than three million tweets during the 2020 United States (US) presidential elections. Affective and cognitive cues were assessed via sentiment analysis. The hypotheses were tested in negative binomial regressions. The authors also scrutinized a subsample of far-famed Twitter users. The final dataset, scraping code, preprocessing and analysis are available in an open repository.

The authors found the prominence of both affective and cognitive cues. For the overall sample, negativity bias was registered, and the tweet’s emotionality was negatively related to engagement. In contrast, in the sub-sample of tweets from famous users, emotionally charged content produced higher engagement. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with many followers. Collective self-representation (“we-talk”) is consistently associated with more likes, comments and retweets in the overall sample and subsamples.

The authors expand the dominating one-sided perspective to social media message processing focused on the peripheral route and hence affective cues. Leaning on the dual process theory, the authors shed light on the effectiveness of both affective (peripheral route) and cognitive (central route) cues on information appeal and dissemination on Twitter during a political event. The popularity of the tweet’s author moderates these relationships.

Economic sanctions imposed by the EU and United States on Russia have brought significant changes into Russian foreign economic policy, in particular leading to deepening cooperation with Asian countries and China in particular. The present contribution aims to shed light on the influence of sanctions on Russian multinational enterprises (MNEs) internationalization toward China using the example of energy and information and communication technology (ICT) industries.

The chapter builds on case study analysis. The choice of sectors allows us to highlight the recent strategic trends in the internationalization of oil and gas industry, dominated by state-owned multinationals, and in ICT by privately owned companies.

Our results provide empirical data for understanding the influence of sanctions on MNEs from the country being under the sanctions. In the case of Russian oil and gas industry and ICTs, research indicates that the shift toward China was not initiated primarily by the sanctions. In both cases, expansion to Asian markets was correlated with business interests in the Chinese market. However, changes in geopolitical and macroeconomic business environment accelerated Russian MNE’s pivot to China, for the purposes of attracting capital and reaching new markets in context of deteriorating relations with western partners. The cases demonstrate a moderating role of the industry in the context of sanctions, helping compensate for the slowdown of economic relations with traditional partners.

The novelty of the chapter is to delineate the consequences of sanctions on MNEs from the country being under sanctions. In this way, it illustrates the role of geopolitical environment in intensifying internationalization of Russian MNEs toward China.