What is he best known for?
The fields of study he is best known for:
- Law
- Politics
- Social science
Francis L. F. Lee spends much of his time researching Politics, Public relations, Surgery, Political economy and Media studies.
His biological study spans a wide range of topics, including Social media and Online and offline.
His study explores the link between Social media and topics such as Social movement that cross with problems in Advertising.
Francis L. F. Lee interconnects Causal chain, Umbrella Movement and Action in the investigation of issues within Public relations.
His studies deal with areas such as Collective efficacy, Development economics, Democracy and Power as well as Political economy.
His studies in Media studies integrate themes in fields like Argument, Credibility and The arts, Cultural economics.
His most cited work include:
- Facebook Use and Political Participation: The Impact of Exposure to Shared Political Information, Connections With Public Political Actors, and Network Structural Heterogeneity (135 citations)
- Cultural Discount and Cross-Culture Predictability: Examining the Box Office Performance of American Movies in Hong Kong (78 citations)
- Learning curve for unilateral endoscopic totally extraperitoneal (TEP) inguinal hernioplasty. (75 citations)
What are the main themes of his work throughout his whole career to date?
Francis L. F. Lee mainly investigates Politics, Media studies, Public relations, Public opinion and Social psychology.
The Politics study combines topics in areas such as Social media, Political economy and Newspaper.
As a part of the same scientific study, he usually deals with the Media studies, concentrating on Social movement and frequently concerns with Umbrella Movement.
His Public relations research is multidisciplinary, incorporating perspectives in Collective action and China.
His China research incorporates elements of Economic growth, Gender studies and Power.
As part of his studies on Social psychology, Francis L. F. Lee often connects relevant subjects like Perception.
He most often published in these fields:
- Politics (30.14%)
- Media studies (21.53%)
- Public relations (19.14%)
What were the highlights of his more recent work (between 2018-2021)?
- Movement (5.74%)
- Politics (30.14%)
- Political economy (11.96%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Movement, Politics, Political economy, Social media and Social psychology.
His Movement study incorporates themes from Law, Political radicalism and Social movement.
His Politics research incorporates themes from Industrial organization and Newspaper.
His Social media study integrates concerns from other disciplines, such as East Asia, Personalization, Political efficacy, Media studies and Advertising.
In general Social psychology study, his work on Incivility often relates to the realm of Context effect, thereby connecting several areas of interest.
His research in Public opinion intersects with topics in Materialism, Demographic economics and Public relations.
Between 2018 and 2021, his most popular works were:
- Hong Kong's Summer of Uprising: From Anti-Extradition to Anti-Authoritarian Protests (25 citations)
- Solidarity in the Anti-Extradition Bill movement in Hong Kong (24 citations)
- Consumptive News Feed Curation on Social Media as Proactive Personalization: A Study of Six East Asian Markets (8 citations)
In his most recent research, the most cited papers focused on:
- Law
- Social science
- Politics
The scientist’s investigation covers issues in Political economy, Social media, Politics, Advertising and East Asia.
Francis L. F. Lee has included themes like Movement, Social movement and Solidarity in his Political economy study.
The various areas that Francis L. F. Lee examines in his Social media study include Political efficacy, Deliberative democracy and Social network.
His Politics study often links to related topics such as Mobilization.
Many of his studies on Advertising apply to Personalization as well.
This overview was generated by a machine learning system which analysed the scientist’s
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