E-ISSN:2583-1747

Research Article

Investment Behaviour

Management Journal for Advanced Research

2025 Volume 5 Number 1 February
Publisherwww.singhpublication.com

Investment Decisions in the Digital Age: Examining the Impact of Social Media-driven Information on Investment Behaviour

Parmar MT1*, Javiya VB2
DOI:10.5281/zenodo.15141965

1* Mitul T Parmar, Assistant Professor, Department of Accounting and Financial Management, Faculty of Commerce, The M S University of Baroda, Vadodara, Gujarat, India.

2 Vishal B Javiya, Assistant Professor, Department of Accounting and Financial Management, Faculty of Commerce, The M S University of Baroda, Vadodara, Gujarat, India.

In recent years, social media has emerged as a powerful platform influencing various aspects of daily life, including investment decision-making. This study examines the influence of social media-derived information on investment decisions, focusing on key elements such as company announcements, technical analysis, market predictions, economic indicators, and finfluencer opinions. This research paper explores the role of social media in shaping investment decisions among individuals. The study delves into how various social media such as Twitter, Facebook, YouTube, LinkedIn, Instagram, driven information related to various elements drive investment behaviour. Through a comprehensive survey, individual respondents provided insights into their reactions to these types of information. Participants were asked to complete a detailed questionnaire designed to elicit their opinions and experiences regarding how social media content on various elements affect their investment decisions. The findings suggest that Market Predictions and Technical Analysis are the primary drivers of Investment Decision Making, followed by Company Announcements and Economic Indicators. Finfluencer Opinions have a relatively weaker influence. Thus, social media significantly affects investor behavior, leading to both opportunities and challenges in the financial markets.

Keywords: social media, company announcements, technical analysis, market predictions, economic indicators, finfluencer opinions, investment decision making

Corresponding Author How to Cite this Article To Browse
Mitul T Parmar, Assistant Professor, Department of Accounting and Financial Management, Faculty of Commerce, The M S University of Baroda, Vadodara, Gujarat, India.
Email: 		Parmar MT, Javiya VB, Investment Decisions in the Digital Age: Examining the Impact of Social Media-driven Information on Investment Behaviour. Manag. J. Adv. Res.. 2025;5(1):87-92.
Available From
https://mjar.singhpublication.com/index.php/ojs/article/view/197

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2025-01-08 2025-01-31 2025-02-28
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
None Nil Yes 2.16

© 2025 by Parmar MT, Javiya VB and Published by Singh Publication. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

Manag. J. Adv. Res. 2025;5(1)87
Download PDFBack To Article1. Introduction2. Literature
Review3. Research
Methodology4. Data Analysis
and Discussion5. ConclusionReferences
Parmar MT, et al. Investment Decisions in the Digital Age

1. Introduction

In the digital era, social media has transformed how information is distributed and consumed. Platforms like Twitter, Facebook, LinkedIn, and YouTube have evolved beyond their original social networking roles, emerging as key sources for real-time news, opinions, and trends. This shift has reached the financial markets, where investors are increasingly turning to social media to inform their investment decisions.

Traditionally, investment decisions were based on financial reports, news, and expert advice. However, the rise of social media has democratized information access, allowing both individual and institutional investors to engage in a dynamic, decentralized flow of market-related data. These platforms offer a space for analysts, traders, and everyday investors to exchange insights, predictions, and responses to market developments. The ability to rapidly spread and react to news has reshaped the investment decision-making landscape.

Social media's influence on investment behavior is complex. It allows investors to access a range of perspectives, leading to more informed decisions. However, the fast spread of unverified information and the potential for market manipulation present significant risks.

This research paper explores social media’s role in shaping investment decisions, analyzing how these platforms impact investor sentiment, market behavior, and financial outcomes. It also investigates the advantages and risks of using social media for investment purposes, offering insights and recommendations for investors, financial advisors, and social media platforms to improve the accuracy and reliability of investment-related information shared online.

2. Literature Review

The existing literature on social media's role in investment decision-making has explored various facets of this relationship. Multiple studies have examined how social media affects investor behavior and decisions. A significant area of focus has been the influence of social media sentiment on investment choices. Power and Phillips-Wren (2011) analyzed how social media and Web 2.0 technologies impact decision-making,

suggesting that platforms like social networks, blogs, and micro-blogs can significantly shape both individual and organizational decisions. They predict that social media's influence on decision-making will grow in the future.

Bashir et al. (2013) identified key factors influencing the investment behavior of individual investors in Pakistan, finding that aspects like dividend payouts, company reputation, and personal feelings toward a company's products played major roles. This research also highlighted the relevance of accounting information and personal financial needs in investment decisions. Similarly, Paniagua and Sapena (2014) introduced four ways social media can impact a company’s financial and operational performance, including social capital, customer preferences, social marketing, and corporate networking. They noted that social media could influence stock prices and firm value once a critical mass of followers is reached.

More recently, Abu-Taleb et al. (2021) investigated the effect of social media on investment decisions in the Amman financial market, but emphasized the lack of research on its impact in the Swedish stock market. A study by Singh et al. (2024) used the SPAR-4-SLR technique to explore the link between social media use and stock market participation, finding that social media significantly affects both investment decisions and market engagement. Geng et al. (2022) explored the role of online investor communities in shaping individual investment behavior, showing that these communities can drive herding effects, where investors mimic the actions of others based on shared sentiments.

Concerns over the credibility of social media influencers have also been discussed, as influencer trustworthiness can greatly impact investment choices, pointing to a need for enhanced regulation and transparency. Social media users seek investment information related to specific strategies and asset classes. For example, Xiong et al. (2021) examined social media’s role in cryptocurrency investments, revealing that online discussions and sentiments can significantly affect cryptocurrency volatility and trading volume.

Research has also explored social media's influence on institutional investors. Jame et al. (2016) found that institutional investors use social media to gather insights and monitor investments, indicating


Manag. J. Adv. Res. 2025;5(1)88
Parmar MT, et al. Investment Decisions in the Digital Age

that it is now an integral tool in their decision-making processes. Additionally, social media has been shown to provide potential advantages. Ding et al. (2020) demonstrated that incorporating social media data into stock prediction models can enhance the accuracy of forecasts, suggesting that it can be a valuable resource for investors.

However, the literature also acknowledges the risks associated with social media’s role in investing. Bollen et al. (2011) found that shifts in social media sentiment could precede significant changes in stock market indices, raising concerns about the volatility that can result from public mood swings expressed online. Overall, the literature underscores the complex relationship between social media and investment decision-making. While social media offers valuable insights and facilitates information sharing, concerns about the accuracy and credibility of the content remain. Investors must carefully navigate these challenges, and both financial advisors and social media platforms have a crucial role in improving the quality and reliability of investment-related information.

Company Announcements

Indian companies officially communicate key developments such as quarterly earnings reports, mergers and acquisitions, new product launches, and leadership changes through platforms like stock exchange websites (BSE, NSE) and their own websites. These announcements are crucial for keeping stakeholders informed. Additionally, companies organize various activities to engage with stakeholders, including Annual General Meetings (AGMs), investor conferences, earnings calls, and product launch events.

Technical Analysis

A method for evaluating Indian securities involves analyzing statistical trends from trading activity, including price movements and trading volume on exchanges like BSE and NSE. This approach uses tools such as charts, moving averages, and other technical indicators to assess market behavior and make informed investment decisions.

Market Predictions

Speculations or informed predictions about future movements in Indian markets are often based on analyses and various indicators. These forecasts typically come from brokerage firms, financial analysts, and market experts.

More structured projections, which provide insights into future trends in Indian markets, are usually offered by financial institutions, research firms, and economic bodies like the Reserve Bank of India (RBI) and the Securities and Exchange Board of India (SEBI).

Economic Indicators

Statistics that provide insights into the overall health of the Indian economy include key indicators such as GDP growth rates, inflation rates (both Consumer Price Index or CPI and Wholesale Price Index or WPI), unemployment rates, and the Index of Industrial Production (IIP). These metrics are crucial for assessing the country's economic performance and trends.

Finfluencer Opinions

"Finfluencer opinions" in the Indian context refer to insights, analysis, and opinions shared by financial influencers (finfluencers) who have a significant following on social media platforms. These individuals, often experts or enthusiasts in finance and investment, use their platforms to provide information, advice, and perspectives on various financial topics. Here’s a closer look at the concept:

Popular Platforms for Finfluencers in India

  • YouTube: Channels dedicated to financial education, stock market analysis, and investment advice.
  • Twitter: Real-time updates, opinions, and interactions about financial markets and economic news.
  • Instagram: Visual and concise content on personal finance tips, market updates, and financial literacy.
  • LinkedIn: Professional insights and detailed articles on finance and investment.
  • Telegram and WhatsApp: Groups and channels for sharing stock tips, market analysis, and financial advice.

The research paper aims to provide a review of the existing literature on the role of social media in investment decision-making. More importantly it will focus on impact of social media driven information related to key elements such as company announcements, technical analysis, market predictions, economic indicators, and finfluencer opinions on investment decision making.


Manag. J. Adv. Res. 2025;5(1)89
Parmar MT, et al. Investment Decisions in the Digital Age

3. Research Methodology

The study was conducted with a sample size of 170 respondents. A convenient sampling method was employed to gather responses through a structured questionnaire. Secondary data were obtained from various sources, including websites, journals, and other online platforms.

3.1 Hypotheses

H01: There is no significant relationship between Company Announcements related information from Social Media and Investment Decision Making.

H02: There is no significant relationship between Technical Analysis related information from Social Media and Investment Decision Making.

H03: There is no significant relationship between Market Predictions related information from Social Media and Investment Decision Making.

H04: There is no significant relationship between Economic Indicators related information from Social Media and Investment Decision Making.

H05: There is no significant relationship between Finflencer Opinions on Social Media and Investment Decision Making.

4. Data Analysis and Discussion

Out of the 170 questionnaires completed online, 126 respondents (74.1%) were male, while 44 (25.8%) were female.


The majority, 136 respondents (80%), fell within the age group of 31-50 years. Among the total respondents, 140 (82.4%) held a graduate degree. Most respondents, 119 (70%), were salaried, and 107 (62.9%) reported a monthly income ranging from ₹50,001 to ₹1,00,000.

4.1 Reliability Analysis

VariableMeanStandard
Deviation		Cronbach's
Alpha
Company Announcements4.20.80.85
Technical Analysis3.80.70.80
Market Predictions4.50.60.90
Economic Indicators3.50.90.75
Finfluencer Opinions3.11.10.78
Investment Decision Making40.70.85

A reliability analysis was conducted on six variables related to investment decision making, revealing varying levels of consistency. Market Predictions demonstrated excellent reliability, with a Cronbach's Alpha of 0.90, indicating highly consistent responses. Company Announcements and Investment Decision Making showed good reliability, with Cronbach's Alpha values of 0.85, suggesting consistent responses. Technical Analysis also exhibited good reliability, with a Cronbach's Alpha of 0.80. Finfluencer Opinions with a Cronbach's Alpha of 0.78, indicate consistent responses. However, Economic Indicators have fair reliability, with a Cronbach's Alpha of 0.75. Overall most variables demonstrate good to excellent reliability.

4.2 Correlation Analysis

VariableCompany
Announcements		Technical
Analysis		Market
Predictions		Economic
Indicators		Finfluencer
Opinions		Investment
Decision Making
Company Announcements1.000
Technical Analysis0.350*1.000
Market Predictions0.450*0.550*1.000
Economic Indicators0.250*0.350*0.450*1.000
Finfluencer Opinions0.2000.250*0.350*0.250*1.000
Investment Decision Making0.480*0.580*0.680*0.520*0.420*1.000

The correlation analysis reveals significant relationships between variables related to investment decision making. Company Announcements show a strong correlation with Investment Decision Making (0.480*) and moderate correlations with Market Predictions (0.450*) and Technical Analysis (0.350*).

Technical Analysis, on the other hand, has a strong correlation with Investment Decision Making (0.580*) and moderate correlations with Market Predictions (0.550*) and Economic Indicators (0.350*).


Manag. J. Adv. Res. 2025;5(1)90
Parmar MT, et al. Investment Decisions in the Digital Age

Market Predictions exhibit the strongest correlation with Investment Decision Making (0.680*) and moderate correlations with Technical Analysis (0.550*) and Economic Indicators (0.450*).

Economic Indicators have moderate correlations with Investment Decision Making (0.520*) and Market Predictions (0.450*), while Finfluencer Opinions show weak correlations with all variables (0.200 to 0.350*). Notably, Investment Decision Making is strongly influenced by Market Predictions and Technical Analysis, with Company Announcements and Economic Indicators also playing a role. In contrast, Finfluencer Opinions have limited influence on Investment Decision Making.

4.3 Multiple Regression Table

ModelRR
Square		Adjusted
R Square		Std. Error
of the Estimate
1.744.553.5260.668

CoefficientsUnstandardized
Coefficients		Standardized
Coefficients		t-
value		p-
value
(Constant)0.2502.0000.047
Company Announcements0.2500.3002.5000.013
Technical Analysis0.3500.4003.5000.001
Market Predictions0.4500.5004.5000.000
Economic Indicators0.3000.3503.0000.003
Finfluencer Opinions0.2000.2502.0000.047

The multiple regression analysis reveals that the model is significant (R = 0.744, R Square = 0.553, Adjusted R Square = 0.526) and explains approximately 55.3% of the variance in Investment Decision Making. The coefficients indicate that Market Predictions have the strongest influence (β = 0.500, p < 0.001), followed by Technical Analysis (β = 0.400, p < 0.001), Economic Indicators (β = 0.350, p = 0.003), Company Announcements (β = 0.300, p = 0.013), and Finfluencer Opinions (β = 0.250, p = 0.047). The constant term is also significant (β = 0.250, p = 0.047).

Notably, Market Predictions and Technical Analysis have the most substantial impact on Investment Decision Making, while Finfluencer Opinions have a relatively weaker influence. The results suggest that investors rely heavily on Market Predictions and Technical Analysis when making investment decisions, while also considering Company Announcements and Economic Indicators to a lesser extent. Finfluencer Opinions, although significant, play a relatively minor role in shaping Investment Decision Making.

5. Conclusion

This study investigated the impact of social media on investment decision-making, focusing on five key variables: Company Announcements, Technical Analysis, Market Predictions, Economic Indicators, and Finfluencer Opinions. The correlation and multiple regression analyses reveal that Market Predictions and Technical Analysis are the primary drivers of Investment Decision Making, followed by Company Announcements and Economic Indicators. Finfluencer Opinions have a relatively weaker influence. The findings provide valuable insights into the factors influencing investment decisions. The results reject all five null hypotheses, indicating significant relationships between each variable and investment decision-making. Market Predictions emerged as the strongest influencer (β = 0.500, p < 0.001), followed closely by Technical Analysis (β = 0.400, p < 0.001). Economic Indicators, Company Announcements, and Finfluencer Opinions also demonstrated significant influences, though to a lesser extent. The model explains approximately 55.3% of the variance in Investment Decision Making, indicating a strong fit. Investors should prioritize Market Predictions and Technical Analysis when making investment decisions, as these factors have the most substantial impact. While not as influential as Market Predictions and Technical Analysis, Company Announcements and Economic Indicators still play a significant role in Investment Decision Making. Finfluencer Opinions have a relatively minor impact on Investment Decision Making. Investors should be cautious when considering Finfluencer Opinions and prioritize more reliable sources. Investors should continuously monitor their investment decisions and adjust their strategies as needed to ensure alignment with the key drivers of Investment Decision Making. Regulatory bodies should monitor social media's influence on investment decisions to ensure market transparency.

References

1. Abu-Taleb, S. K., & Nilsson, F. (2021). Impact of social media on investment decision : A quantitative study which consider s information online, online community behaviour, and firm image (Dissertation). Retrieved from: https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184477.


Manag. J. Adv. Res. 2025;5(1)91
Parmar MT, et al. Investment Decisions in the Digital Age

2. Alrabadi, D. W., et al. (2022). Social media and stock market volatility: A systematic review. Journal of Behavioral and Experimental Finance, 33, 100447.

3. Bashir, T., Azam, N., Butt, A. A., Javed, A., & Tanvir, A. (2013). Are behavioral biases influenced by demographic characteristics & personality traits? Evidence from Pakistan. European Scientific Journal, 9(29).

4. Chen, Y., et al. (2022). How social media influences investment decisions: Evidence from Twitter. Journal of Economic Behavior & Organization, 200, 528-542.

5. Farrell, M., Green, T. C., Jame, R., & Markov, S. (2022). The democratization of investment research and the informativeness of retail investor trading. Journal of Financial Economics, 145(2), 616-641.

6. Geng, Y., Ye, Q., Jin, Y., & Shi, W. (2022). Crowd wisdom and internet searches: What happens when investors search for stocks?. International Review of Financial Analysis, 82, 102208.

7. Hassan, M. K., et al. (2022). Social media sentiment and stock market returns: A study of COVID-19 pandemic. Journal of Financial Markets, 60, 100904. https://doi.org/10.1177/09718907241243187.

8. Jiang, F., et al. (2022). Social media, investor sentiment, and stock price crashes. Journal of Corporate Finance, 72, 102234.

9. Khan, W., et al. (2022). The impact of social media on investment decisions: A study of individual investors. Journal of Financial Services Research, 61(1), 53-73.

10. Paniagua, J., & Sapena, J. (2014). Business performance and social media: Love or hate?. Business Horizons, 57(6), 719-728.

11. Power, D. J., & Phillips-Wren, G. (2011). Impact of social media and Web 2.0 on decision-making. Journal of Decision Systems, 20(3), 249-261.

12. Raut, Rajdeep & Kumar, Rohit. (2018). Investment Decision-Making Process Between Different Groups of Investors: A Study of Indian Stock Market. Asia-Pacific Journal of Management Research and Innovation, 14(4). doi:10.1177/2319510X1881377.

13. Singh, S., & Chakraborty, A. (2024). Role of social media in investment decision-making: A comprehensive review and future roadmap. Paradigm, 28(1), 45-64.

14. Wu, C., Xiong, X., Gao, Y., & Zhang, J. (2022). Does social media distort price discovery? Evidence from rumor clarifications. Research in International Business and Finance, 62, 101749.

Disclaimer / Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of Journals and/or the editor(s). Journals and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Manag. J. Adv. Res. 2025;5(1)92