Corporate Social Responsibility and Social Media: Comparison between Developing and Developed Countries
Abstract
:1. Introduction
1.1. CSR Communication and Social Needs
1.2. Specifics of CSR in Developing Countries
2. Materials and Methods
- Content filtration: as the analysis only focused on hashtags, all words that were not preceded by the symbol # were removed. This led to a dataset that consisted purely of hashtags (i.e., words beginning with the symbol #).
- Content segmentation: a total of 24,339 messages contained geolocations in the form of latitude and longitude. Google Maps Geolocation API [66] was used to transform these into addresses (street, city and state). Only the state was used for segmentation. Based on this segmentation, we confirmed that 9712 messages were sent from developed countries and 14,627 from developing countries. Countries were categorised as developing and developed according to the classification established by the International Monetary Fund, which has also been adopted by Herzer [67], Lotz and Blignaut [68], Mendonça and Tiberto [69], and the World Economic Outlook in 2019 [70]. This classification ranks countries into the two following groups: those with advanced economies, which are considered to be developed countries; and those with developing economies and an emerging market, which are considered to be developing countries. Countries are classified according to the three following auxiliary criteria: (1) income per person, (2) the diversification of exports and (3) the degree of integration into the global financial system.
- Content transformation: subsequently, all letters were transformed to lower-case letters to prevent potential duplicities (e.g., the software might consider #CSR, #Csr or #csr as three different hashtags). A further correction was made to break up strings of connected hashtags, e.g., “#csr#philanthropy” was converted to “#csr #philanthropy”. The dataset was imported into Gephi 0.9.2, where a hashtag network was created based on their interdependence (see Figure 2).
- Hashtag reduction: to process a hashtag reduction and remove micro-communities, it was first necessary to detect communities. The presence of many communities is caused by an extensive number of hashtags that contained local hashtags and hashtags created by the users themselves.
- Data mining: the following methods were used to describe the network.
- Frequency: frequency is a value that expresses the hashtag frequency within a network.
- Edge weight: edge weight is a value that indicates the number of connections between two specific hashtags.
- Eigenvector centrality: eigenvector centrality is an extension of degree centrality which measures the influence of hashtags in a network. The value is calculated based on the premise that connections to hashtags with high values (hashtags with a high degree of centrality) have a greater influence than links with hashtags of similar or lower values. A high eigenvector centrality score means that a hashtag is connected to many hashtags with a high value, and is calculated as follows:
- Modularity: the most complex networks contain nodes that are mutually interconnected to a larger extent than they are connected to the rest of the network. Groups of such nodes are called communities [71]. Modularity represents an index that identifies the cohesion of communities within a given network [72]. The idea is to identify node communities that are mutually interconnected to a greater degree than other nodes. Networks with high modularity show strong links between nodes inside modules, but weaker links between nodes in different modules [73]. The component analysis then identifies the number of different components (in the case of community modularity) in the network based on the modularity detection analysis [74], as follows:
3. Results
3.1. Community Analysis: Developed Countries
3.2. Developing Countries
3.3. Community Analysis—Developing Countries
4. Discussion and Implication
- A low value of modularity was identified in both developed and developing countries, indicating that these are non-polarized areas of communication. This is a very important finding because based on this value, it can be argued that there are no CSR groups that have been communicated separately and are polarised to another group. On the contrary, these groups showed very low polarisation, which means that the individual areas can be communicated in parallel or subsequently, depending on each other.
- The second most communicated area in developed countries is the area of sustainability. This can be used in the field of cooperation between companies that offer services and products in the field of sustainability (sustainable innovation, the environment, climate change, etc.; for more, see [52]) and companies in developed countries that communicate in the field of sustainability in connection with CSR. In other words, it is possible to prepare sustainability products for these companies, which can then communicate in the field of CSR.
- In the developed countries area, the ‘start-up with CSR’ community was extracted. This means that start-up companies that want to be responsible are starting to form in developed countries. This segment includes the opportunity for interested stakeholders and the ‘how to address’ segment, and has a high potential to implement and continuously extend CSR activities in the core value of companies. This segment also represents an opportunity for governments, which should take advantage of start-ups’ interest in responsible business and support it with incentives or tax breaks.
- Based on the analysis of communication from both developed and developing countries, it can be said that there is a different style of communication for each area. This must be taken into account in the field of strategic marketing in order to adapt the individual campaigns of global companies based on their targeting by region.
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Hashtag | F | EV | Hashtag | F | EV | ||
---|---|---|---|---|---|---|---|
1. | #charity | 1198 | 0.976611 | 11. | #giveback | 481 | 0.881463 |
2. | #sustainability | 847 | 1 | 12. | #education | 476 | 0.906601 |
3. | #socialgood | 598 | 0.895748 | 13. | #dogood | 448 | 0.90359 |
4. | #philanthropy | 594 | 0.85258 | 14. | #marketing | 435 | 0.877589 |
5. | #corporatesocialresponsibility | 592 | 0.957848 | 15. | #donate | 427 | 0.788761 |
6. | #socialimpact | 552 | 0.906127 | 16. | #innovation | 372 | 0.842975 |
7. | #fundraising | 550 | 0.853937 | 17. | #socent | 349 | 0.809912 |
8. | #community | 512 | 0.94754 | 18. | #givingback | 322 | 0.772759 |
9. | #volunteer | 490 | 0.869003 | 19. | #business | 318 | 0.963728 |
10. | #nonprofit | 486 | 0.866115 | 20. | #volunteering | 312 | 0.770115 |
#Charity | Edge Weight | #Sustainability | Edge Weight | #Socialgood | Edge Weight |
---|---|---|---|---|---|
#philanthropy | 458 | #socialimpact | 141 | #charity | 393 |
#fundraising | 452 | #environment | 125 | #philanthropy | 375 |
#socialgood | 393 | #education | 113 | #fundraising | 331 |
#nonprofit | 371 | #socialgood | 106 | #socialimpact | 330 |
#donate | 366 | #changemakers | 102 | #dogood | 324 |
#dogood | 318 | #ecofriendly | 96 | #nonprofit | 314 |
#socialimpact | 293 | #green | 96 | #donate | 304 |
#education | 288 | #business | 93 | #socent | 276 |
#volunteer | 270 | #recycle | 93 | #causes | 265 |
#socent | 249 | #sustainable | 89 | #activism | 261 |
#change | 242 | #giveback | 88 | #change | 254 |
#activism | 233 | #philanthropy | 88 | #4charity | 234 |
#4charity | 224 | #community | 87 | #innovation | 230 |
#causes | 221 | #innovation | 81 | #volunteer | 217 |
#innovation | 200 | #activism | 80 | #nptech | 180 |
Name of the Community | Size of the Community | Key Hashstags |
---|---|---|
hilanthropic responsibility | 31.02 | #charity; #socialgood; #philanthropy; #socialimpact; #fundraising; #volunteer; #nonprofit; #giveback; #dogood; #donate |
Environment sustainability | 27.35 | #corporatesocialresponsibility; #community; #green; #environment; #recycle; #sustainable; #corporate; #socialresponsibility; #eco; #nature |
Pleasure from working | 25.71 | #business; #love; #instagood; #responsibility; #art; #work; #happy; #social; #travel; #fun |
Start-up with CSR | 15.92 | #education; #startup; #entrepreneur; #inspiration; #fashion; #leadership; #entrepreneurship; #startuplife; #branding |
Hashtag | F | EV | Hashtag | F | EV | ||
---|---|---|---|---|---|---|---|
1. | #charity | 1253 | 1 | 11. | #sustainability | 568 | 0.867136 |
2. | #socialgood | 817 | 0.84515 | 12. | #philanthropy | 550 | 0.803319 |
3. | #education | 815 | 0.9939 | 13. | #activism | 536 | 0.685032 |
4. | #love | 758 | 0.95407 | 14. | #fundraising | 447 | 0.777071 |
5. | #nonprofit | 749 | 0.855128 | 15. | #giveback | 430 | 0.865403 |
6. | #donate | 702 | 0.883272 | 16. | #india | 424 | 0.888853 |
7. | #corporatesocialresponsibility | 700 | 0.932505 | 17. | #community | 424 | 0.908422 |
8. | #volunteer | 679 | 0.917067 | 18. | #instagood | 420 | 0.944384 |
9. | #dogood | 639 | 0.862776 | 19. | #change | 411 | 0.781201 |
10. | #ngo | 631 | 0.905223 | 20. | #children | 407 | 0.904628 |
#Charity | Edge Weight | #Socialgood | Edge Weight | #Education | Edge Weight |
---|---|---|---|---|---|
#socialgood | 580 | #nonprofit | 616 | #charity | 287 |
#nonprofit | 515 | #dogood | 590 | #donate | 258 |
#activism | 471 | #charity | 580 | #socialgood | 232 |
#dogood | 461 | #activism | 505 | #fundraising | 230 |
#donate | 413 | #donate | 465 | #nonprofit | 218 |
#fundraising | 398 | #philanthropy | 435 | #dogood | 203 |
#philanthropy | 395 | #volunteer | 382 | #giveback | 200 |
#change | 348 | #fundraising | 373 | #children | 199 |
#volunteer | 347 | #change | 368 | #change | 197 |
#causes | 319 | #causes | 365 | #activism | 181 |
#education | 287 | #socent | 276 | #ngo | 180 |
#socent | 257 | #cause | 262 | #philanthropy | 160 |
#children | 220 | #socialimpact | 261 | #volunteer | 149 |
#socialimpact | 216 | #impact | 248 | #fundraiser | 148 |
#impact | 188 | #education | 232 | #socialimpact | 131 |
Name of the Community | Size of the Community | Key Hashtags |
---|---|---|
Social and environmental responsibility | 44.79% | #corporatesocialresponsibility; #community; #instagood; #travel; #environment; #social; #indonesia; #givingback; #socialresponsibility |
Philanthropic responsibility | 41.32% | #charity; #socialgood; #education; #nonprofit; #donate; #volunteer; #dogood; #ngo; #sustainability; #philanthropy |
Reputation management | 13.88% | #business; #marketing; #awareness; #entrepreneur; #recycle; #sustainable; #corporate; #digitalmarketing; #workshop; #branding; #advertising; #creative; #socialentrepreneur |
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Kvasničková Stanislavská, L.; Pilař, L.; Margarisová, K.; Kvasnička, R. Corporate Social Responsibility and Social Media: Comparison between Developing and Developed Countries. Sustainability 2020, 12, 5255. https://doi.org/10.3390/su12135255
Kvasničková Stanislavská L, Pilař L, Margarisová K, Kvasnička R. Corporate Social Responsibility and Social Media: Comparison between Developing and Developed Countries. Sustainability. 2020; 12(13):5255. https://doi.org/10.3390/su12135255
Chicago/Turabian StyleKvasničková Stanislavská, Lucie, Ladislav Pilař, Klára Margarisová, and Roman Kvasnička. 2020. "Corporate Social Responsibility and Social Media: Comparison between Developing and Developed Countries" Sustainability 12, no. 13: 5255. https://doi.org/10.3390/su12135255
APA StyleKvasničková Stanislavská, L., Pilař, L., Margarisová, K., & Kvasnička, R. (2020). Corporate Social Responsibility and Social Media: Comparison between Developing and Developed Countries. Sustainability, 12(13), 5255. https://doi.org/10.3390/su12135255