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Social Media, Economic Well-Being and Satisfaction with Democracy in Africa

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Mathieu Juliot Mpabe Bodjongo and Moustapha Fofana

Submitted: 11 April 2025 Reviewed: 24 April 2025 Published: 20 January 2026

DOI: 10.5772/intechopen.1010728

Elections in the Global South and North IntechOpen
Elections in the Global South and North A Comprehensive Overview Edited by Opeyemi Idowu Aluko

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Elections in the Global South and North - A Comprehensive Overview

Opeyemi Idowu Aluko

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Abstract

This chapter aims to examine the effect of social media and economic well-being on citizens’ satisfaction with democracy in Africa. The analysis focuses on a sample of 35,590 people living in 34 African countries, drawn from data collected by Afrobarometer (2019). The econometric results, obtained using an ordered probit model with an endogenous variable, show that following news via social media significantly reduces satisfaction with democracy. Furthermore, people with a high level of objective or subjective economic well-being are less likely to be satisfied with democracy.

Keywords

  • social media
  • poverty
  • satisfaction
  • democracy
  • Africa

1. Introduction

This chapter examines the influence of social media and economic well-being on citizens’ satisfaction with democracy in Africa. To achieve this objective, an ordered probit with an endogenous covariate is used and applied to the Afrobarometer 2019 data. The rationale for this study is the importance of citizens’ satisfaction with democracy in assessing the success of a democratic system in implementing effective public policies to improve people’s welfare [1]. Sen [2] considers democracy as an end in itself (intrinsic view) or as a means to improve social welfare (instrumental view). Traditionally, the notion of democracy has been associated with individual freedom, civil liberties and electoral competition. Democracy is supposed to a tool for improving the quality of public goods and services by making politicians respond to the expectations of their constituents in order to secure their re-election [3]. Other authors have shown that democracy contributes to improving of people’s living conditions and life satisfaction [4, 5, 6].

Mbembe [7] denounces the poor progress made by African countries in terms of democracy. However, Sindjoun [8] argues that it is important not to overlook the contradictory dynamics of the construction of new political legitimacies issues in several African states. According to Afrobarometer (2019), about 68.01% of Africans absolutely support democracy, 12.98% think that democracy is not preferable in some situations, while 14.43% are totally opposed to democracy. In addition, some 44.51% of Africans are fairly or very satisfied with democracy. At the same time, some 34.31% of Africans consider their personal living conditions to be fairly or very good, while only 13.70% of Africans do not live in poverty.

In addition, about 34.39% of Africans have access to the Internet and 34.72% are subscribers to social media platforms such as Facebook, WhatsApp, Twitter and TikTok. The media is an important source of political information and a bridge between governments and citizens, as most people get their political information through different types of media use. This political information in the media can penetrate interpersonal political discussions and change people’s interest in politics, thus influencing citizens’ assessment of democracy. With the development of information technology, politics is increasingly mediated through different types of media use [9]. As Boulianne [10] points out, different types of media use (e.g. newspapers, television, radio and Internet) have different relationships with political interest because of differences in the effort required to use information sources, their ability to share information and the diversity of their content.

The literature has focused on the factors that explain citizens’ satisfaction with democracy [11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]. Among these factors, some studies have focused on the influence of economic well-being [11, 13, 14, 15, 16, 18, 19]. Others have focused on the impact of the Internet [17] and, to our knowledge, only one study has examined the influence of information gathered through social media [12]. However, their findings show some differences, indicating that the debate on this topic is still ongoing.

In terms of geographical coverage, while these studies have been conducted in Asian countries and Europe, very little attention has been paid to African countries. There is often heterogeneity between these regions in terms of culture, population, language and economic and human development indicators [24]. The few studies that have examined at the explanatory factors of satisfaction with democracy in Africa [3, 25] have not examined the influence of social media or economic well-being. Moreover, Wantchekon and Taylor [3] used a sample of 16 countries from the 2005 Afrobarometer database and concluded that their results do not “allow conclusions to be drawn about how citizens of countries with autocratic regimes or civil wars would have reacted to democracy if it had been installed in their country”. Indeed, it should be noted that the authors excluded from their analysis countries that are not democracies or that are in a situation of political crisis or civil war. However, they acknowledge that “one cannot exclude a priori the existence of latent national characteristics that influence the establishment of a democratic regime and the appreciation of democracy by the average citizen once it is established”. Bratton and Mattes [25] based their study on survey data from three African countries: South Africa in 1997, Ghana in 1999 and Zambia in 1996.

To fill this gap, we will use the 2019 Afrobarometer database, which consists of 34 countries, for our study. It offers a diverse range in terms of democracy, including countries with low levels of democracy and countries in political crisis or civil war. Our sample is fairly representative of all African countries (63%) and the population size of the countries in our sample represents more than 70% of Africa’s total population.1 Economically, the GDP per capita in our sample is USD 5680 in purchasing power parity terms, while the average for sub-Saharan Africa is USD 4069.2 Furthermore, our study uses the ordered probit model with an endogenous covariate to correct for endogeneity bias in the relationship between economic well-being and satisfaction with democracy.

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2. Literature review

2.1 Social media and satisfaction with democracy

Monnoyer-Smith [27] reminds us that every new communication technology has been seen as a potential way to mobilise citizens and modernise institutions. Seminal studies on the political Internet have tended to focus on the “impact” that new information and communication technologies (NICTs) could have on democracy, justified by the fact that “the role of the Internet as a tool for monitoring, dissemination and mobilisation (circulation of information, increase in petitioning practices) is indeed increasingly central to the functioning of democracy” [28]. NICTs are often seen as a solution to the crisis of representation [29]. Social media, particularly Facebook and Twitter, allow citizens to directly question politicians, who can then interact with them directly [30]. Social media are thus potentially a very rich place for debate, even if the reality is often very different. Social media allow citizens to express themselves in a very horizontal way, to bring to the fore protests that were not heard before, and they are also a tool for emancipation: by taking over the word and the image, it is possible to become a real actor [31, 32].

In the early 2000s, digital technology was hailed for its ability to revitalise democracy. It seemed inconceivable to question the compatibility between social media and democracy. At the time, social media (Facebook and Twitter) were seen as a great opportunity for democratic revitalisation. A few years later, however, pessimism prevails and concerns are growing; digital technology is often strongly criticised for facilitating the spread of false information. Social media can be detrimental to democracy by further polarising opinions, facilitating manipulation and exacerbating tensions [32, 33]. Through its “troll factories”, Russia was able to interfere in the US and French presidential elections. In 2016, more than 126 million Americans were exposed to content from Kremlin propaganda services at least once on Facebook. Governments and opposition political parties around the world have increasingly set up Internet influence services [34].

Disinformation campaigns conducted via social media often seek to change citizens’ perceptions of their government’s policies. Their primary aim is to sow confusion in people’s minds, undermine trust in democratic institutions, and incite social unrest and violence [33]. They also often encourage the spread of conspiracy theories, creating “epistemological disorder” and exhausting the critical mind by making truth and lies indistinguishable. Fake news spreads faster than real information and continues to circulate even after being contradicted by the mainstream media.

It is important to remember that when we talk about social media, we are talking about private platforms whose aim is to make a profit and therefore to maximise engagement and interaction. The business model of these platforms is based on advertising; the challenge is to maximise engagement and interaction. To do this, these private platforms have an incentive to favour those speeches that provoke the most epidermal reactions and, consequently, the “virality” of the content. The aim is not to promote a calm debate based on well thought-out ideas. Moreover, it is the audience that gives credit on social media. It is the audience that gives content visibility and places it at the heart of the network. But what gives content this visibility is not so much its relation to a truth based on empirical evidence or verification, but rather purely quantitative criteria. And when people respond to a tweet, or even repost it, it is not necessarily because they agree with it, it is sometimes to denounce or mock content that is considered grotesque, absurd or outrageous, but this gives it even more visibility and, therefore, more credit. It is, therefore, not easy to construct quality democratic debates when epidermal passions dominate and the truth is, in a way, devalued.

Some authors [35, 36] have been able to classify computer propaganda campaigns into three categories. The first is aimed at polarising citizens on specific issues, such as immigration, racism, terrorism and homosexuality. The aim is to get groups of voters to confront each other in anger on social media and in the streets. The second is to promote or discredit particular politicians. Any public figure on the national stage can either be attacked by or benefit from highly automated or fake social media accounts. The third is to discourage citizens from voting. Voter suppression is a common messaging strategy that targets voters who are likely to support a particular candidate in an election. For example, voters may be informed that polling day has been postponed, that they can vote by text message or that their polling station has been moved.

Empirically, Boulianne [37] shows that social media contributes to increasing citizens’ political participation. Bailard [17] confirms the clear, consistent and significant impact of the Internet on democratic satisfaction. However, the Internet is correlated with higher satisfaction in advanced democracies and is associated with lower satisfaction in countries with weak democratic practices. Ceron and Memoli [12] find that Internet use per se has no effect on satisfaction with democracy. Chang [1] also finds that satisfaction with democracy declines significantly with Internet access. The study by Ceron and Memoli [12] is one of the few that highlights the influence of social media on satisfaction with democracy. However, they argue that social media has a negative effect on satisfaction with democracy.

2.2 Economic well-being and satisfaction with democracy

At the macroeconomic level, some studies have shown that an increase in GDP significantly improves the democratisation of a country’s political environment [38]. In contrast, Wagner et al. [39] provide evidence to the contrary. At the micro-level, the debate is less clear-cut. Bratton and Mattes [25] show that improvements in citizens’ current living conditions significantly increase their satisfaction with democracy. The economic well-being indicator is also subjective as it measures satisfaction with current living conditions. To measure satisfaction with democracy in South Africa and Ghana, individuals are asked: “How satisfied or dissatisfied are you with the way democracy is working?”. In Zambia, satisfaction with democracy was measured by averaging satisfaction scores for specific attributes of democracy such as political freedoms, elections and the performance of elected representatives. These indicators do not appear to be equivalent and the authors acknowledge the value of standardising the measurement of satisfaction with democracy. This standardisation has been carried out in the Afrobarometer 2019 database.

Using the 2005 Afrobarometer database, Wantchekon and Taylor [3] do not measure the direct impact of economic well-being on satisfaction with democracy. Using an ordered logit, they show that objective economic well-being, in contrast to subjective well-being, does not significantly affect the instrumental view of democracy. According to these two authors, the instrumental view is measured by the importance of democracy in promoting the values of (i) peace and national unity, (ii) development, (iii) solidarity, reciprocity and cooperation, (iv) good governance, (v) autonomy and independence and (vi) respect for human rights. It is negatively related to satisfaction with democracy. It should be recalled that to measure subjective economic well-being, respondents were asked how they perceived their economic situation in relation to that of others in their social environment. To measure objective economic well-being, respondents were asked whether they had gone without food one or more times in the past year.

Outside Africa, Anderson and Guillory [40] found that individual income as a group had a positive and significant effect on satisfaction with democracy in a sample of 11 European countries. On the other hand, in a country-by-country analysis, these two authors found that individual income had a positive and significant effect on satisfaction with democracy in only three countries. Furthermore, the overall economic performance of the country significantly increased satisfaction with democracy, whether analysed globally or on a country-by-country basis.

Harmel and Tan [15] also found, using the OLS method, that an increase in individual life satisfaction significantly increased support for the one-party system in China. Chinese people are currently enjoying material satisfaction. However, this influence on life satisfaction is insignificant when the variable to be explained is the individual’s perception that multipartyism creates chaos and crisis in the country.

Using an ordered logit model, Zhai [18] showed that citizens’ economic satisfaction has mixed effects on political satisfaction in China. In fact, on the one hand, improving economic satisfaction significantly increases satisfaction with civil liberties and political rights. To measure satisfaction with civil liberties and political rights, respondents were asked to indicate how satisfied they were with the right to vote, the right to participate in any type of organisation, the right to assemble and demonstrate, the right to be informed about the work and functions of the government, freedom of expression and the right to criticise the government. On the other hand, an increase in economic satisfaction has no significant effect on satisfaction with the current level of democracy in China. Economic satisfaction is a composite index derived from three indicators: satisfaction with housing, satisfaction with living conditions and satisfaction with household income.

Using a logit model, Zhai [19] finds that economic status does not significantly affect satisfaction with democracy in China. The author measures the economic status of individuals using an indicator that captures the ability of income to cover needs satisfactorily. Kang [16] found similar results for South Korea, using probit with Heckman selection bias correction. He used this method because of the endogeneity bias that exists between satisfaction with democracy and satisfaction with the welfare system.

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3. Methodology

3.1 Data

Data for this study comes from the Afrobarometer database (2019). Information was collected from 34 African countries,3 comprising 45,824 individuals. As our study focused on individuals who responded to questions about satisfaction with democracy and participation in elections, the sample size was 35,590 individuals.

Afrobarometer uses national probability samples, which are designed to be representative of all citizens of voting age in a given country. The aim is to give every adult citizen an equal and known chance of being selected for an interview, which is achieved by (i) using random selection methods at each stage of the sampling process and (ii) sampling at all stages with a probability proportional to the size of the population, as far as possible, to ensure that larger (i.e. more populous) geographical units have a proportionally higher chance of being selected in the sample [24].

The sample universe normally includes all citizens aged 18 and over. People living in institutions, such as students in halls of residence, patients in hospitals and people in prisons or old people’s homes, are usually excluded. Sometimes, people living in areas considered inaccessible due to conflict or insecurity are also excluded. The sample design is a multi-stage, stratified, clustered regional probability sample. Specifically, the sample is first stratified by the main sub-national government unit (state, province, region, etc.) and by urban or rural location [41].

The Afrobarometer network is an independent, non-partisan research project carried out by CDD, IDASA and MSU. Implemented through a network of national partners, Afrobarometer measures economic conditions and the political atmosphere in African countries [41]. The questionnaire is standardised to facilitate cross-country comparisons. The countries covered by the 2019 surveys are listed in Table A1 in the Appendix.

3.2 Econometric model

To identify explanatory factors of satisfaction with democracy in cross section, some studies have used ordered logit or probit models [11, 13, 14], simple logit or probit models [19] and the probit with Heckman selection bias correction [16]. However, these models do not account for endogeneity or simultaneity bias between variables. Therefore, given the nature of the variable that captures satisfaction with democracy, our econometric model was chosen to be an ordered probit with an endogenous covariate. This model has the advantage of accounting for the endogeneity and simultaneity bias between economic well-being and satisfaction with democracy. The data we have do not provide information on the timing of these two behaviours. For example, it is not known whether economic well-being precedes satisfaction with democracy. However, the expression of direct simultaneity between these two behaviours requires that this question be answered. The endogeneity of explanatory variables is often a problem in behavioural econometrics. Theoretically, in the presence of endogeneity, the expectation of the error term conditional on the explanatory variable is non-zero, and the usual estimators are subject to bias [41].

The model is as follows:

SDEM=Yi=vhifkh−1<Xiβ+WbjhβC+εi≤khE1
SDEM=Yi=01234There is notademocracynotatallsatisfied with democracynot very satisfied with democracyQuite satisfied with democracyVery satisfied with democracyE2

SDEM is the variable that captures the individual’s level of satisfaction with democracy. We note that h takes the values 0, 1, 2, 3 and 4. Also, we note that vh<vm for h<m. k0 takes the value −∞ and kH takes the value +∞. X is the vector of exogenous variables.

The level of economic well-being (EW) of an individual is captured through two indicators: BEO and BES. The first is an objective economic well-being indicator calculated from a composite poverty index. It takes the value 0 if the individual is not poor, 1 if their poverty level is low, 2 if their poverty level is moderate and 3 if their poverty level is high. The second is an indicator of subjective economic well-being, which informs about individual’s perception of their living conditions. It has a value of 0 if living conditions are very bad, 1 if they are fairly bad, 2 if they are neither bad nor good, 3 if they are fairly good and 4 if they are very good. The endogenous multinomial variable is BE:

BE=Wbjh=vbjhifkbjh−1<Zbjiαbj+ϵbji≤kbjhE3

The values vbj1....vbjB are real numbers so that vbjh<vbjm for h<m. kbj0 takes the value −∞ and kbjB takes the value +∞. Z is the vector of exogenous variables. The errors ϵb1i...ϵbBi follow a multivariate normal distribution with mean 0 and covariance:

∑b=1ρb12∗∗ρb1Bρb121∗∗ρb2B∗∗ρb1B∗∗ρb2B∗∗∗∗∗∗∗∗1E4

PGECON is a variable that measures the economic performance of the current government. It is an index constructed from seven indicators: (i) good management of the economy, (ii) improvement of living conditions, (iii) job creation, (iv) price stability, (v) reduction of income inequality, (vi) construction and maintenance of roads and bridges and (vii) provision of electricity. It takes the value 0 if the performance is low, 1 if it is medium and 2 if it is high.

PGSOS is the variable that provides information about the social and security performance of the current government. It is an index constructed from five indicators: (i) meeting the expectations of young people, (ii) improving basic health services, (iii) meeting education needs, (iv) providing water services and (v) increasing food availability. It takes the value 0 if the performance is low, 1 if it is medium and 2 if it is high.

PGINST is the variable that provides information on the institutional performance of the current government. It is an index constructed from seven indicators: (i) control of corruption, (ii) prevention of violence during elections, (iii) prevention and resolution of community conflicts, (iv) prevention and fight against terrorist attacks, (v) promotion of women’s rights and opportunities, (vi) reduction of crime and (vii) protection of human rights. It takes the value 0 if it is low, 1 if it is medium and 2 if it is high.

TELE is the variable that informs whether the individual informs themselves through television. It takes the value 1 if yes and 0 if no.

DAY is the variable that indicates whether the individual gets information from the print media. It takes the value 1 if yes and 0 if no.

SOME is the variable that informs whether the individual is informed on social media. It takes the value 1 if yes and 0 if no.

INT is the variable that provides information on the individual’s access to the Internet. It has a value of 1 if the individual has access to the Internet and 0 if they do not.

SEX is the variable that informs about the sex of the individual. It takes the value 1 if they are male, and 0 of they are female.

ZON is the variable that provides information on the individual’s place of residence. It has a value of 1 if they live in an urban area and 0 if he/she lives in a rural area.

AGE is the variable that captures the age of the individual. It takes the value 0 if he is young (age between 18 and 35) and 1 if they old (over 35).

EDU is the variable that makes it possible to assess the level of education of the individual. It has a value of 0 if they are illiterate, 1 if they have primary education, 2 if they have secondary education and 3 if they have higher education.

REL is the variable that informs about the religious affiliation of the individual. It takes the value 2 if they are Muslim, 1 if they are Christian and 0 in the opposite case.

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4. Results

Table 1 shows that 48.10% of citizens are either fairly or very satisfied with the level of democracy in their country. The government’s performance is rated positively by 5.2% of people for economic issues, 10.60% for social issues and 16.20% for institutional and security issues. In addition, poverty is widespread in Africa, with only 14.20% of people escaping its grip. Finally, it is noted that 32.10% of people are subscribed to social media.

VariablesAverageStandard deviationMinimumMaximum
SDEM
The country is not a democracy0.0170.13101
Not at all satisfied with democracy0.2210.41501
Not very satisfied with democracy0.2810.45001
Quite satisfied with democracy0.3260.46901
Very satisfied with democracy0.1550.36201
PGECO
Very bad0.6230.48501
Quite bad0.3250.46801
Fairly good or very good0.0520.22201
PGSOS
Very bad0.3870.48701
Quite bad0.5070.50001
Fairly good or very good0.1060.30801
PGINS
Very bad0.2940.45501
Quite bad0.5450.49801
Fairly good or very good0.1620.36801
SEX
Woman0.4770.49901
Male0.5230.49901
ZON
Rural area0.5580.49701
Urban area0.4420.49701
AGE
Young person0.4870.50001
Elderly person0.5130.50001
EDU
Illiterate0.1940.39601
Primary education0.2950.45601
Secondary education0.3570.47901
Higher education0.1550.36101
REL
Other religions0.1090.31201
Christians0.5660.49601
Muslims0.3240.46801
BEO
High level of poverty0.1750.38001
Average poverty level0.3110.46301
Low poverty level0.3720.48301
Not poverty0.1420.34901
BES
Very bad0.2160.41201
Quite bad0.2590.43801
Neither good nor bad0.1920.39401
Fairly good0.2690.44401
Very good0.0640.24501
TELE
No0.4010.49001
Yes0.5990.49001
DAY
No0.6570.47501
Yes0.3430.47501
SOME
No0.6780.46701
Yes0.3220.46701
INT
No0.5470.49801
Yes0.4530.49801

Table 1.

Descriptive statistics.

The econometric results are analysed in Table 2. The correlation coefficient ρ (BIECO, SEMO) between the satisfaction with democracy equation and the economic well-being equation is statistically significant at the 1% threshold level. Some unobservable individual characteristics simultaneously affect a citizen’s chances of having a high level of economic well-being and of being satisfied with democracy. This suggests that the probability of having a high level of economic well-being positively affects the probability of being satisfied with democracy and vice versa. There are thus complementary relationships between economic well-being and satisfaction with democracy. It therefore seems useful to estimate these two equations simultaneously.

Model 1Model 2
CoefficientStandard deviationCoefficientStandard deviation
Equation of satisfaction with democracy
PGECO (ref: very bad)
Quite bad0.328***0.0440.421***0.032
Fairly good or very good0.609***0.0900.730***0.073
PGSOS (ref: very bad)
Quite bad0.298***0.0380.283***0.033
Fairly good or very good0.440***0.0680.444***0.062
PGINS (ref: very bad)
Quite bad0.142***0.0380.195***0.033
Fairly good or very good0.243***0.0620.289***0.051
SEX (ref: Female sex)−0.0200.028−0.0230.027
ZON (ref: Rural area)−0.0100.051−0.102***0.028
AGE (ref: young)0.0420.0270.0010.027
EDU (ref: Illiterate)
Primary education0.098*0.0570.0010.040
Secondary education0.155**0.0750.0170.040
Higher education0.256**0.1170.122**0.052
REL (ref: Other religions or no religion)
Chétien−0.0190.0580.0420.055
Muslim0.0430.0560.0450.054
BEO (ref: high poverty level)
Average poverty level−0.407**0.188
Low poverty level−0.801**0.355
Not poverty−1.293**0.555
BES (ref: Very bad)
Quite bad−0.489***0.093
Neither good nor bad−0.770***0.146
Fairly good−1.139***0.207
Very good−1.667***0.310
TELE (ref: No)−0.121***0.031−0.082***0.027
DAY (ref: No)−0.0060.028−0.0180.025
SOME (ref: No)−0.107***0.036−0.092***0.032
INT (ref: No)0.0010.032−0.0030.029
Economic well-being equation
PGECO (ref: very bad)
Quite bad−0.0010.0330.266***0.032
Fairly good or very good0.0140.0730.398***0.072
PGSOS (ref: very bad)
Quite bad0.252***0.0340.195***0.033
Fairly good or very good0.374***0.0630.353***0.062
PGINS (ref: very bad)
Quite bad−0.0300.0340.127***0.034
Fairly good or very good−0.0670.0520.091*0.051
SEX (ref: Female sex)−0.064**0.027−0.060**0.026
ZON (ref: Rural area)0.226***0.028−0.0350.027
AGE (ref: young)0.051*0.027−0.045*0.026
EDU (ref: Illiterate)
Primary education0.268***0.0410.0160.040
Secondary education0.418***0.0390.0540.038
Higher education0.711***0.0440.288***0.043
REL (ref: Other religions or no religion)
Christian−0.107*0.0570.0590.056
Muslim−0.0270.0560.0080.055
SDEM
cut1−2.3340.081−2.3360.078
cut2−0.8090.172−0.9360.107
cut3−0.0520.237−0.2440.148
cut40.9560.3270.6790.210
BE
cut1−0.5010.068−0.6050.067
cut20.4670.0680.1760.067
cut31.6680.0700.6360.067
1.7900.069
ρ (BE. SDEM)0.501***0.1640.624***0.082

Table 2.

Result of the ordered probit model in panel data.

NB: ***, ** and * represent significance at 1%, 5% and 10% respectively.

Improving the economic, social and institutional performance of the government contributes significantly to increasing the economic well-being of individuals. Several studies have shown that economic well-being increases with reduced corruption [42], maintenance of national security [43], social protection [44] and infrastructure [45]. Men and Christians are relatively less likely to have high levels of economic well-being. However, Teka et al. [46] show that men are more willing to have higher incomes than women. Levels of economic well-being are relatively and significantly higher among those living in urban areas, the elderly and the educated people. With regard to residence, Castaneda et al. [47] find that 80.10% (respectively 75.70%) of people living in extreme poverty (or moderate poverty, respectively) live in rural areas worldwide. Regarding education, Teka et al. [46] show that educated people are more likely to escape the poverty trap. With regard to age, Castaneda et al. [47] find that 74.60% (respectively 67.80%) of people under 35 years of age live in extreme poverty (respectively moderate poverty).

Only three variables do not significantly affect satisfaction with democracy in Africa, namely gender, age and religious affiliation of the individual. With regard to gender, our results contradict empirical work that argues that women are less likely to be highly satisfied with democracy [48, 49, 50]. With regard to age, it contradicts studies showing that satisfaction decreases significantly with age [11, 50, 51].

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5. Discussions

The coefficients of the variables “BEO” and “BES” are negative and significant, indicating that individuals’ satisfaction with democracy decreases with economic well-being. This result is contrary to that of Kang [16] and Zhai [19]. This result can be explained by the social comparison mechanism and the coping mechanism. In terms of social comparison, individuals tend to compare their income with that of socially close individuals. They are satisfied with democracy when the comparison is in their favour and not satisfied when they envy the income of others. In terms of coping mechanisms, a person who experiences an increase in income may be immediately satisfied with democracy, but after some time, they get used to their new income, and their satisfaction with democracy returns to its original level. Graham and Pettinato [52] show that in Latin America, the rich people are relatively more supportive of democracy, while the poor people are less willing to support the political transition. The poorest, most marginalised and most vulnerable people in developing countries are the most resistant to change [53]. The difficulties in achieving democracy are thus said to result from the induced effects of poverty, as the vital need to satisfy basic needs first pushes “higher” needs, such as political freedoms and autonomy, into the background. Poor people are characterised by a lesser predisposition to the virtues of individual freedoms (especially the freedom to choose their representatives) due to their lack of financial and material resources [54, 55]. Poor people are said to be more conservative and attached to traditional institutions (state, family) and the moral principles they promote (authority, discipline, etc.).

The sign of the variable “SOME” is negative and significant at the 1% level, indicating that satisfaction with democracy decreases among people who subscribe to social media. Our result highlights the negative influence of social media, which do not promote increased political knowledge, political awareness [56, 57], or participation in elections [58]. Furthermore, social networks can lead to the radicalisation of some citizens [59].

The sign of the variable “TELE” is also negative and significant at the 1% level, suggesting that citizens with access to television news are less likely to be highly satisfied with democracy. This result contradicts Ceron and Memoli [12], who show that satisfaction with democracy increases, and Chang [1] who argues that television does not significantly affect satisfaction with democracy. Despite the existence of media regulatory bodies in Africa, television media are increasingly being accused of breaching of professional standards and publishing of misinformation, which may be detrimental to the growth of democracy.

The modalities of the variables “PGECO”, “PGSOC” and “PGINS” are positive and significant at the 1% level, indicating that the economic, social and institutional performance of the government is conducive to a significant increase in satisfaction with democracy. This result highlights the role of the government’s economic, social, institutional and security performance. Foa et al. [60] show that economic exclusion is an important driver of dissatisfaction in developed democracies. Higher levels of unemployment and wealth inequality are associated with increased dissatisfaction in both absolute and relative terms, that is, a growing gap between younger and older people’s assessment of democratic functioning. Several other studies have shown that high GDP, lower income inequality and satisfaction with the country’s economic situation favour higher satisfaction with democracy [11, 13, 14, 49, 50, 61]. Lühiste [50] shows that satisfaction with a country’s welfare system significantly increases satisfaction with democracy. Bauer [51] finds that in the Netherlands and Switzerland, unemployed people are less likely to have high levels of satisfaction with democracy. Christmann and Torcal [13] find a similar result for Spain. Finally, Kang [16] shows that unemployment has no significant effect on satisfaction with democracy.

Some empirical work [39, 61] confirms that control over corruption, for example, increases satisfaction with democracy. Stockemer and Sundström [62] find that an individual’s perceptions of police and judicial corruption influence satisfaction with democracy. Ariely [63] argues that satisfaction with democracy rises significantly as the quality of public administration improves. However, the same finding does not hold for general indicators of macro-level corruption; macro-level corruption does not significantly affect satisfaction with democracy. Norris [64] shows that satisfaction with democracy decreases significantly as electoral malpractice increases, as measured by the following factors: (i) preventing certain opposition leaders from running, (ii) threats of violence against voters during the election, (iii) electoral corruption and (iv) state media favouring only the ruling party.

The coefficients of the modalities of the variable “EDU” are positive and significant, indicating that satisfaction with democracy increases with the level of education. Several empirical studies [13, 16, 48, 49, 50, 51, 61] have shown that satisfaction with democracy increases significantly with the level of education. As education allows individuals to develop a critical awareness of the world around them, to assert themselves as actors in this world, and to become aware of socio-environmental realities that need to be transformed, a politically educated or literate population is more inclined to live and thrive in a democracy [65].

The sign of the coefficient on the variable “ZON” is negative and significant in model 2, indicating that people living in urban areas are less likely to be highly satisfied with democracy. Norris [64] argues that satisfaction with democracy increases significantly with the degree of urbanisation.

In order to analyse the robustness of our results, we have divided the sample into two parts: former French colonies on the one hand and countries not colonised by France on the other. Using the same econometric model, the results in Table A2 are largely similar to those in Table 2.

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6. Conclusion

This study highlights the influence of social media and economic well-being on citizens’ satisfaction with democracy in Africa. Methodologically, we used descriptive statistical techniques and an ordered probit model with an endogenous variable using the Afrobarometer (2019) database.

The econometric results show that following news via social media significantly reduces satisfaction with democracy, and people with a high level of objective or subjective economic well-being are less likely to be satisfied with democracy.

Social media gives every citizen the impression of being able to speak to the whole world. But in reality, everyone is comforted by their own opinions. It is not a place of democracy. It is not structurally designed for that. Rather, it is a powerful tool that, among other things, allows citizens to be recruited and directed to the websites and other digital platforms of political parties, where a consensual and collective debate can be built. Social media is a medium like any other, an interesting tool for communication, but it is not the place where democracy is lived. States and political parties need to invest in social media to sensitise citizens against the disinformation campaigns that often flood social media.

African countries need to build more inclusive democracies. Democracy can only satisfy the poor if it gives them opportunities to start their own businesses or enterprises. The quality of democratic representation depends in part on the ability of minority social groups (especially the poor) to participate in elections and be represented in political arenas.

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Additional information

JEL code: D72, L86, I30, N47, P37, P48

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Appendix

CountryPopulation sizeGDP per capita in US dollars
Benin13,301,6943649
Botswana2,350,66716,304
Burkina Faso21,382,6592394
Cabo Verde589,4516717
Cameroon28,524,1754065
Ivory Coast29,389,1505850
eSwatini1,113,2769730
Gabon2,284,91215,175
Gambia2,100,0002281
Ghana32,372,8895971
Guinea1,976,1872900
Kenya54,685,0515211
Lesotho2,177,7402521
Liberia5,214,0301563
Madagascar27,534,3541607
Malawi20,308,5021638
Mali20,137,5272329
Mauritius1,386,12923,035
Morocco36,561,8138853
Mozambique30,888,0341347
Namibia2,678,19110,038
Niger23,605,7671303
Nigeria219,463,8625408
São Tomé and Príncipe213,9484451
Senegal16,082,4423840
Sierra Leone6,807,2771773
South Africa56,978,63514,624
Sudan45,500,0004066
Tanzania62,092,7612836
Togo8,283,1892334
Tunisia11,811,33511,282
Uganda44,000,0002467
Zambia19,077,8163556
Zimbabwe14,829,9882329
Total858,896,174193,447

Table A1.

List and profile of countries in the sample [62].

Source: World Bank [26].

Model 3Model 4Model 5Model 6
Former Non-French coloniesFormer French colonies
CoefficientStandard deviationCoefficientStandard deviationCoefficientStandard deviationCoefficientStandard deviation
Equation of satisfaction with democracy
PGECO (ref: very bad)
Quite bad0.263***0.0630.464***0.0560.374***0.0540.093*0.050
Fairly good or very good0.434***0.1041.012***0.1260.823***0.1650.164*0.097
PGSOS (ref: very bad)
Quite bad0.372***0.0450.160***0.0570.164**0.0750.095*0.050
Fairly good or very good0.520***0.0790.282**0.1110.266**0.1340.0810.086
PGINS (ref: very bad)
Quite bad0.083*0.0440.362***0.0540.311***0.0620.0110.044
Fairly good or very good0.1040.0700.457***0.0890.477***0.0930.0550.066
SEX (ref: Female sex)0.0010.036−0.0470.043−0.0560.0440.092***0.033
ZON (ref: Rural area)0.0250.047−0.105**0.050−0.0170.092−0.0280.035
AGE (ref: young)0.0170.0340.0600.0440.110**0.0460.0440.034
EDU (ref: Illiterate)
Primary education0.137**0.069−0.122**0.056−0.0300.0870.0310.068
Secondary education0.135*0.074−0.0180.0660.0630.108−0.0200.065
Higher education0.264***0.0990.0150.0920.1760.192−0.224***0.070
REL (ref: Other religions or no religion)
Chétien−0.126*0.0730.0540.093−0.0150.111−0.0810.069
Muslim−0.1180.0800.166*0.0890.278***0.098−0.0120.071
BEO (ref: high poverty level)
Average poverty level−0.671***0.150−0.2540.303
Low poverty level−1.234***0.292−0.6560.548
Not poverty−1.985***0.448−1.0110.866
BES (ref: Very bad)
Quite bad−0.393**0.1880.820***0.055
Neither good nor bad−0.540*0.3131.253***0.080
Fairly good−0.963**0.4361.893***0.101
Very good−1.409**0.6502.853***0.149
TELE (ref: No)−0.102***0.036−0.0490.044−0.093*0.048−0.065**0.030
DAY (ref: No)−0.0200.030−0.0630.048−0.0290.052−0.0200.027
SOME (ref: No)−0.076**0.039−0.106*0.060−0.120*0.064−0.075**0.033
INT (ref: No)0.0340.035−0.0630.055−0.0660.0580.0260.031
Economic well-being equation
PGECO (ref: very bad)
Quite bad−0.0640.0430.362***0.0510.088*0.0510.218***0.042
Fairly good or very good0.0150.0910.636***0.122−0.0600.1240.284***0.089
PGSOS (ref: very bad)
Quite bad0.215***0.0450.208***0.0510.279***0.0530.173***0.044
Fairly good or very good0.299***0.0810.394***0.1000.446***0.1020.311***0.079
PGINS (ref: very bad)
Quite bad0.0190.0450.237***0.0530.0190.0550.075*0.044
Fairly good or very good−0.0620.0670.0800.0810.0340.0830.1020.065
SEX (ref: Female sex)−0.059*0.034−0.0310.042−0.0520.043−0.077**0.034
ZON (ref: Rural area)0.180***0.035−0.0030.0470.290***0.048−0.0510.034
AGE (ref: young)0.0190.035−0.0370.0410.116***0.042−0.0530.034
EDU (ref: Illiterate)
Primary education0.143**0.070−0.0240.0540.242***0.0550.0330.069
Secondary education0.270***0.0660.101*0.0570.359***0.0590.0120.065
Higher education0.548***0.0690.231***0.0720.736***0.0750.263***0.067
REL (ref: Other religions or no religion)
Christian−0.209***0.0720.0020.093−0.230**0.0950.0700.071
Muslim−0.271***0.075−0.0120.0860.287***0.0880.0210.073
cut1−2.4950.109−2.4090.127−2.3070.132−0.3630.192
cut2−1.2850.186−0.6380.211−0.4090.2030.7110.126
cut3−0.6110.2630.0940.2840.3700.2791.3140.105
cut40.2590.3691.1150.3911.4610.3942.1000.104
cut1−0.9650.100−0.5550.101−0.0360.103−0.6530.098
cut20.0620.0990.2910.1010.9040.1030.0880.098
cut31.2760.1010.8110.1012.1220.1080.5120.098
cut 42.0750.1071.6120.100
ρ (BE. SDEM)0.680***0.1280.545***0.1630.418*0.256−0.763***0.051

Table A2.

Result of the ordered probit model in panel data: former French colonies vs. countries not colonised by France.

NB: ***, ** and * represent significance at 1%, 5% and 10%, respectively.

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Notes

  • Read Mpabe [24]. Estimate based on World Bank statistics (2022): Look at Table A1.
  • Read Mpabe [24]. Estimate based on World Bank statistics (2022): Look at Table A1.
  • Table A1 presents the list of countries in the sample.

Written By

Mathieu Juliot Mpabe Bodjongo and Moustapha Fofana

Submitted: 11 April 2025 Reviewed: 24 April 2025 Published: 20 January 2026

© 2026 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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