Analyzing The Impact of Social Media Buy Recommendations on Saudi Stock Market Reactions: A Bert-Based Sentiment and Network Analysis Approach
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Date
2026
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Saudi Digital Library
Abstract
Social media has become part of the daily rhythm of financial markets, its actual
influence on prices remains debated. This dissertation examines whether buy recommendations
posted by Saudi-focused social media analysts on Twitter/X are associated with short-term stock
market reactions in the Tadawul exchange. The central question is straightforward: when
influential online analysts issue concentrated buy signals, do prices and trading activity respond
in measurable ways?
To address this, I combine multiple empirical strategies in a triangulated research design.
Fixed-effects panel regressions estimate the association between sentiment measures, analyst
exposure, abnormal returns and volume while accounting for firm-level and time-specific
factors. Propensity score matching is used to compare exposed and non-exposed stock-days with
similar observable characteristics, helping reduce selection concerns and strengthening causal
interpretation. An event-study framework aligns returns around recommendation bursts to
examine dynamic price adjustments within clearly defined exposure windows, helping isolate the
timing of market responses. Each method approaches the question from a slightly different angle.
The patterns suggest that analyst activity is strongly linked to short-lived increases in trading
volume and modest return movements. Effects appear concentrated around exposure shocks and
tend to dissipate within days, which consistent with attention-driven responses. Pre-event drift
hints that analysts often post during periods of existing market stress, complicating clean causal
interpretation.
To complement the quantitative analysis, qualitative interviews with retail investors
explore how credibility, repetition, and network visibility are perceived to influence decision-
making. Investors describe using informal mental checklists before acting on recommendations.
Their accounts help contextualize the statistical findings and suggest that social media effects
operate through attention and trust.
Overall, the findings suggest that social media recommendations can redirect attention
and temporarily intensify trading, especially in retail-driven markets. The influence appears
situational, shaped by credibility, timing, and existing sentiment. These patterns are consistent
with a short-term causal influence that is conditioned by market context and investor attention.
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Keywords
Social Media Analysis, Data Science, Sentiment, Tadawul, Saudi Stock Market, Network Analysis, Propensity score matching
