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Dr Chedia Dhaoui

Dr Chedia Dhaoui

Lecturer
Business School
School of Information Systems and Technology Management

Chedia Dhaoui is a Lecturer at the School of Information Systems and Technology Management UNSW Business School, Sydney Australia. Chedia holds a PhD in Marketing from the Faculty of Business and Economics, Macquarie University, and a PhD in Business Intelligence from the Université de Lorraine, France. Through her applied research in digital marketing and business intelligence, Chedia seeks to excel in Social Media Analytics, emotion AI and AI for Business Analytics.

Her research interests cover the dynamics of consumer and brand engagement in online social media environments, mobile marketing, and the application of AI-.technologies for emotion detection and analysis. Chedia's research is data-driven using very large social media datasets gathered from online social networking platforms using advanced data analytics techniques to turn big data into actionable insights. Chedia created Insight Social Networks back in 2012 as a consultancy firm with one main objective: "creating value with social media data".

She publishes her research in peer-reviewed academic journals including the International Journal of Research in Marketing and the Journal of Consumer Marketing, and presented her research at several conferences including Australian and New Zealand Marketing Academy Conference (ANZMAC), American Marketing Association (AMA), and Marketing Science. 
Phone
+61-2-9348 0195
E-mail
c.dhaoui@unsw.edu.au
Location
Room 2110, Quadrangle Building
  • Book Chapters | 2014
    Dhaoui C, 2014, 'What social media marketing content is best to engage consumers?: A content analysis of Facebook brand pages', in Computer-Mediated Marketing Strategies: Social Media and Online Brand Communities, pp. 134 - 156, http://dx.doi.org/10.4018/978-1-4666-6595-8.ch006
  • Journal articles | 2023
    Gu W; Chan KW; Kwon J; Dhaoui C; Septianto F, 2023, 'Informational vs. emotional B2B firm-generated-content on social media engagement: Computerized visual and textual content analysis', Industrial Marketing Management, 112, pp. 98 - 112, http://dx.doi.org/10.1016/j.indmarman.2023.04.012
    Journal articles | 2021
    Dhaoui C; Webster CM, 2021, 'Brand and consumer engagement behaviors on Facebook brand pages: Let's have a (positive) conversation', International Journal of Research in Marketing, 38, pp. 155 - 175, http://dx.doi.org/10.1016/j.ijresmar.2020.06.005
    Journal articles | 2017
    Dhaoui C; Webster CM; Tan LP, 2017, 'Social media sentiment analysis: lexicon versus machine learning', Journal of Consumer Marketing, 34, pp. 480 - 488, http://dx.doi.org/10.1108/JCM-03-2017-2141
  • Conference Papers | 2017
    Dhaoui C; Webster C; Tan L, 2017, 'Brand interventions and emotional dynamics in online consumer-to-consumer conversations: An empirical investigation', Florida, USA, presented at Winter AMA Conference, Florida, USA, 17 February 2017 - 19 February 2017
    Conference Papers | 2017
    Dhaoui C; Webster C; Tan L, 2017, 'Longitudinal Analysis of Online Consumer Disengagement Patterns in Times of Crisis', California, USA, presented at The 39th Annual ISMS Marketing Science Conference, California, USA, 07 June 2017 - 10 June 2017
    Conference Papers | 2016
    Dhaoui C; Webster C; Tan L, 2016, 'Sentiment analysis for brand-related social media conversations', Christchurch, New Zealand, presented at Australian and New Zealand Marketing Academy Conference (ANZMAC), Christchurch, New Zealand, 05 December 2016 - 07 December 2016

Australian Postgraduate Award (APA), Australian Government, 2014-2017, 3 years doctoral research

Australian Government conference presentation fund (2014-2017)

Research fund from industry CIFRE (Conventions Industrielles de Formation par la Recherche), 2003-2008, with the University of Lorraine, Nancy, France

My Teaching

INFS5730 Social Media Analytics in Practice

INFS3830 Social Media Analytics

INFS3822 Artificial Intelligence for Business Analytics

COMM1190 Data, Insights, Decisions

ZZBU6601 General Analytics Capstone